View by area
Also show archived
2024
, No other information
A Survey of Robotic Language Grounding: Tradeoffs Between Symbols and Embeddings 2024
Vanya Cohen, Jason Xinyu Liu, Raymond Mooney, Stefanie Tellex, David Watkins, International Joint Conference on Artificial Intelligence (IJCAI) (2024).
Asynchronous Evolution of Deep Neural Network Architectures 2024
Jason Liang, Hormoz Shahrzad, Risto Miikkulainen, Applied Soft Computing, Vol. 152 (2024), pp. 111209. Also arXiv:2308:04102.
CAPE: Corrective Actions from Precondition Errors using Large Language Models 2024
Shreyas Sundara Raman, Vanya Cohen, Ifrah Idrees, Eric Rosen, Raymond Mooney, Stefanie Tellex, and David Paulius, International Conference on Robotics and Automation (ICRA) (2024).
CAT-BENCH: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans 2024
Yash Kumar Lal, Vanya Cohen, Nathanael Chambers, Niranjan Balasubramanian, Raymond Mooney, Empirical Methods in Natural Language Processing (EMNLP) (2024).
CONTRADOC: Understanding Self-Contradictions in Documents with Large Language Models 2024
Jierui Li, Vipul Raheja, Dhruv Kumar, North American Chapter of the Association for Computational Linguistics (NAACL) (2024).
Deductive Systems for Logic Programs with Counting 2024
Jorge Fandinno and Vladimir Lifschitz, unpublished.
Deductive Systems for Logic Programs with Counting: Preliminary Report 2024
Jorge Fandinno and Vladimir Lifschitz, To Appear In Proceedings of the 17th International Conference on Logic Programming and Non-monotonic Reasoning, 2024.
Discovering Effective Policies for Land-Use Planning with Neuroevolution 2024
Risto Miikkulainen, Olivier Francon, Daniel Young, Elliot Meyerson, Clemens Schwingshackl, Jacob Bieker, Hugo Cunha, and Babak Hodjat, arXiv:2311.12304 (2024). (A shorter version appeared in the Proceedings of the NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning).
Distilling Algorithmic Reasoning from LLMs via Explaining Solution Programs 2024
Jierui Li and Raymond Mooney, preprint (2024).
Domain-Independent Lifelong Problem Solving through Distributed Alife Actors 2024
Babak Hodjat, Hormoz Shahrzad, and Risto Miikkulainen, Artificial Life, Vol. 30 (2024), pp. 359-276.
EVOTER: Evolution of Transparent Explainable Rule-sets 2024
Hormoz Shahrzad, Babak Hodjat, and Risto Miikkulainen, ACM Transactions on Evolutionary Learning and Optimization (2024).
From Sensory Input to Cognitive Maps: Exploring the Significance of Spatial Representations in Artificial Hippocampal Models 2024
Margaret Cordelia von Ebers, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
Generative AI: An AI Paradigm Shift in the Making? 2024
Risto Miikkulainen, AI Magazine (2024), pp. 1-3. https://doi.org/10.1002/aaai.12155.
GPU-Accelerated Rule Evaluation and Evolution 2024
Hormoz Shahrzad and Risto Miikkulainen, arXiv:2406.01821 (2024).
Locally Tight Programs 2024
Jorge Fandinno, Vladimir Lifschitz and Nathan Temple, Theory and Practice of Logic Programming (2024).
Measuring Sound Symbolism in Audio-visual Models 2024
Wei-Cheng Tseng, Yi-Jen Shih, David Harwath, Raymond Mooney, IEEE Spoken Language Technology (SLT) Workshop (2024).
Multimodal Contextualized Semantic Parsing from Speech 2024
Jordan Voas, Raymond Mooney, David Harwath, Association for Computational Linguistics (ACL) (2024).
Natural Language Can Help Bridge the Sim2Real Gap 2024
Albert Yu, Adeline Foote, Raymond Mooney, and Roberto Martín-Martín, Robotics, Science and Systems (RSS) (2024).
NeuroComb: Improving SAT Solving with Graph Neural Networks 2024
Wenxi Wang, Yang Hu, Mohit Tiwari, Sarfraz Khurshid, Kenneth McMillan, Risto Miikkulainen, In Proceedings of the International Conference on Learning Representations, 2024. (also arXiv:2110.14053).
Optimizing the Design of an Artificial Pancreas to Improve Diabetes Management 2024
Ashok Khanna, Olivier Francon, and Risto Miikkulainen, arXiv:2402.07949 (2024).
Semantic Density: Uncertainty Quantification in Semantic Space for Large Language Models 2024
Xin Qiu, Risto Miikkulainen, In Proceedings of the 38th Conference on Neural Information Processing Systems, 2024. (also arXiv:2405.13845).
Sparse Meets Dense: A Hybrid Approach to Enhance Scientific Document Retrieval 2024
Priyanka Mandikal, Raymond Mooney, The 4th Workshop on Scientific Document Understanding, AAAI (2024).
Unlocking the Potential of Global Human Expertise 2024
Elliot Meyerson, Olivier Francon, Darren Sargent, Babak Hodjat, and Risto Miikkulainen, In Proceedings of the 38th Conference on Neural Information Processing Systems (NeurIPS 2024), 2024.
Using context to adapt to sensor drift 2024
Jamieson Warner, Ashwin Devaraj, and Risto Miikkulainen, In Proceedings of the International Conference on Development and Learning (ICDL 2024), 2024. (also arXiv:2003.07292).
When is Tree Search Useful for LLM Planning? It Depends on the Discriminator 2024
Ziru Chen, Michael White, Raymond Mooney, Ali Payani, Yu Su, Huan Sun, Association for Computational Linguistics (ACL) (2024).
A Novel Control Law for Multi-joint Human-Robot Interaction Tasks While Maintaining Postural Coordination 2023
Keya Ghonasgi, Reuth Mirsky, Adrian M Haith, Peter Stone, and Ashish D Deshpande, 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (2023).
Accelerating Evolution Through Gene Masking and Distributed Search 2023
Hormoz Shahrzad and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 972-980, 2023. (Also arXiv:2302.06745).
Accelerating Evolution Through Gene Masking and Distributed Search 2023
Hormoz Shahrzad, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
AutoInit: Analytic Signal-Preserving Weight Initialization for Neural Networks 2023
Garrett Bingham and Risto Miikkulainen, In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023. (also arXiv:2021.08958).
“Female Astronaut: Because sandwiches won’t make themselves up there!": Towards multi-modal misogyny detection in memes 2023
Smriti Singh, Amritha Haridasan, Raymond Mooney, Association of Computational Linguistics (ACL), Workshop on Online Abuse and Harms (WOAH) (2023).
Benchmarking Reinforcement Learning Techniques for Autonomous Navigation 2023
Zifan Xu, Bo Liu, Xuesu Xiao, Anirudh Nair, and Peter Stone, In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA 2023), London, England, May 2023.
Causal Policy Gradient for Whole-Body Mobile Manipulation 2023
Jiaheng Hu, Peter Stone, and Roberto Martin-Martin, In Robotics: Science and Systems (RSS2023), Daegu, Republic of Korea, July 2023.
D-Shape: Demonstration-Shaped Reinforcement Learning via Goal Conditioning 2023
Caroline Wang, Garrett Warnell, and Peter Stone, In Proceedings of the 22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS), London, UK, May 2023.
Directly Optimizing Evaluation Metrics to Improve Text to Motion 2023
Yili Wang, Masters Thesis, Department of Computer Science, UT Austin.
DM$^2$: Decentralized Multi-Agent Reinforcement Learning via Distribution Matching 2023
Caroline Wang, Ishan Durugkar, Elad Liebman, and Peter Stone, In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI-23), Washington, D.C., February 2023.
Efficient Activation Function Optimization through Surrogate Modeling 2023
Garrett Bingham and Risto Miikkulainen, In Proceedings of the 23rd Conference on Neural Information Processing Systems (NeurIPS 2023), 2023.
Evolutionary Supervised Machine Learning 2023
Risto Miikkulainen, In Handbook of Evolutionary Machine Learning, W. Banzhaf, P. Machado, and M. Zhang (Eds.), New York, 2023. Springer.
Evolving Deep Neural Networks 2023
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, Babak Hodjat, To Appear In Artificial Intelligence in the Age of Neural Networks and Brain Computing (second edition), R. Kozma, C. Alippi, Y. Choe, and F. Morabito (Eds.), New York, 2023. Elsevier.
Evolving GAN Formulations for Higher Quality Image Synthesis 2023
Santiago Gonzalez, Mohak Kant, and Risto Miikkulainen, To Appear In Artificial Intelligence in the Age of Neural Networks and Brain Computing (second edition), R. Kozma, C. Alippi, Y. Choe, and F. C. Morabito (Eds.), New York, 2023. Elsevier. Als...
Evolving Strategies for Competitive Multi-Agent Search 2023
Erkin Bahceci, Riitta Katila, and Risto Miikkulainen, arXiv:2306.10640 (2023).
Explaining Competitive-Level Programming Solutions using LLMs 2023
Jierui Li, Szymon Tworkowski, Yingying Wu, Raymond Mooney, Association of Computational Linguistics (ACL), Natural Language Reasoning and Structured Explanations Workshop (2023).
External Behavior of a Logic Program and Verification of Refactoring 2023
Jorge Fandinno, Zachary Hansen, Yuliya Lierler, Vladimir Lifschitz, Nathan Temple, Theory and Practice of Logic Programming (2023).
From Felicitous Models to Answer Set Programming 2023
Vladimir Lifschitz, In Kit Fine on Truthmakers, Relevance, and Non-Classical Logic, 2023. Springer.
Kinematic coordinations capture learning during human–exoskeleton interaction 2023
Keya Ghonasgi, Reuth Mirsky, Nisha Bhargava, Adrian M Haith, Peter Stone, and Ashish D Deshpande, Scientific Reports, Vol. 13 (2023), pp. 10322.
Learning Deep Semantics for Test Completion 2023
Pengyu Nie, Rahul Banerjee, Junyi Jessy Li, Raymond Mooney and Milos Gligoric, International Conference on Software Engineering (2023).
Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways 2023
Jinsoo Park, Xuesu Xiao, Garrett Warnell, Harel Yedidsion, and Peter Stone, In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA 2023), London, England, May 2023.
MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection 2023
Jiaxun Cui, Xiaomeng Yang, Mulong Luo, Geunbae Lee, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, and Yuandong Tian, In The Eleventh International Conference on Learning Representations (ICLR), Kigali, Rwanda, May 2023.
Metric Residual Networks for Sample Efficient Goal-Conditioned Reinforcement Learning 2023
Bo Liu, Yihao Feng, Qiang Liu, and Peter Stone, In Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), Washington, DC, US, February 2023.
Model-Based Meta Automatic Curriculum Learning 2023
Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yuqian Jiang, Bo Liu, and Peter Stone, In The Second Conference on Lifelong Learning Agents (CoLLAs 2023), Montreal, Canada, August 2023.
Modeling Bilingualism as a Dynamic Phenomenon in Healthy and Neurologically Affected Speakers Across the Lifespan (Commentary) 2023
Claudia Penaloza, Uli Grasemann, Risto Miikkulainen, Swathi Kiran, Language Learning, Vol. . (2023). https://doi.org/10.1111/lang.12566.
Motion Planning (In)feasibility Detection using a Prior Roadmap via Path and Cut Search 2023
Yoonchang Sung and Peter Stone, In Robotics: Science and Systems (RSS2023), Daegu, Republic of Korea, July 2023.
Neuroevolution Tutorial 2023
Risto Miikkulainen, No other information
Omega-Completeness of the Logic of Here-and-There and Strong Equivalence of Logic Programs 2023
Jorge Fandinno and Vladimir Lifschitz, In Proceedings of the 20th International Conference on Principles of Knowledge Representation and Reasoning, 2023.
On Heuer’s Procedure for Verifying Strong Equivalence 2023
Jorge Fandinno, Vladimir Lifschitz, In Proceedings of European Conference on Logics in Artificial Intelligence, 2023.
On Program Completion, with an Application to the Sum and Product Puzzle 2023
Vladimir Lifschitz, Theory and Practice of Logic Programming (2023).
Optimizing Neural Networks through Activation Function Discovery and Automatic Weight Initialization 2023
Garrett Bingham, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Pandemic Resilience: Developing an AI-calibrated Ensemble of Models to Inform Decision Making 2023
GPAI, Technical Report, Global Partnership on Artificial Intelligence.
Reward (Mis)design for autonomous driving 2023
W. Bradley Knox, Alessandro Allievi, Holger Banzhaf, Felix Schmitt, and Peter Stone, Artificial Intelligence, Vol. 316 (2023).
SAGEViz: SchemA GEneration and Visualization 2023
Sugam Devare, Mahnaz Koupaee, Gautham Gunapati, Sayontan Ghosh, Sai Vallurupalli, Yash Kumar Lal, Francis Ferraro, Nathanael Chambers, Greg Durrett, Raymond Mooney, Katrin Erk, Niranjan Balasubramanian, Empirical Methods in Natural Language Processing (EMNLP) Demo Track (2023).
Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search 2023
Xin Qiu and Risto Miikkulainen, In Proceedings of the International Conference on Machine Learning (ICML-2023), , 2023. Also arXiv:2210.14016.
Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning 2023
Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuqian Jiang, Yuke Zhu, Peter Stone, and Shiqi Zhang, In International Conference on Intelligent Robots and Systems, Detroit, USA, October 2023.
Text-to-SQL Error Correction with Language Models of Code 2023
Ziru Chen, Shijie Chen, Michael White, Raymond Mooney, Ali Payani, Jayanth Srinivasa, Yu Su, Huan Sun, In Proceedings of the Association for Computational Linguistics (ACL), January 2023.
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications 2023
Serena Booth, W Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, and Alessandro Allievi, In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), Washington, D.C., February 2023.
Using Both Demonstrations and Language Instructions to Efficiently Learn Robotic Tasks 2023
Albert Yu, Raymond J. Mooney, International Conference on Learning Representations (2023).
Using Planning to Improve Semantic Parsing of Instructional Texts 2023
Vanya Cohen, Raymond Mooney, Association of Computational Linguistics (ACL), Natural Language Reasoning and Structured Explanations Workshop (2023).
VaryNote: A Method to Automatically Vary the Number of Notes in Symbolic Music 2023
Juan M. Huerta, Bo Liu, and Peter Stone, In Bridge after the turmoil - The 16th International Symposium, CMMR 2023, Tokyo, Japan, November 13-17, 2023, Tokyo, Japan, November 2023.
What AI Can Do for Neuroscience: Understanding How the Brain Represents Word Meanings 2023
Nora Aguirre-Celis and Risto Miikkulainen, In What AI Can Do: Strengths and Limitations of Artificial Intelligence, Manuel Cebral-Loureda, Elvira G. Rincon-Flores, and Gildardo Sanchez-Ante (Eds.), pp. 401-417, 2023. CRC Press.
What is the Best Automated Metric for Text to Motion Generation? 2023
Jordan Voas, Yili Wang, Qixing Huang, Raymond Mooney, In ACM SIGGRAPH Asia, December 2023.
What is the Best Automated Metric for Text to Motion Generation? 2023
Jordan Voas, Masters Thesis, Department of Computer Science, UT Austin.
A Rule-based Shield: Accumulating Safety Rules from Catastrophic Action Effects 2022
Shahaf Shperberg, Bo Liu, Allessandro Allievi, and Peter Stone, In Proceedings of the 1st Conference on Lifelong Learning Agents (CoLLAs), Montreal, Canada, August 2022.
A Survey of Ad Hoc Teamwork Research 2022
Reuth Mirsky, Ignacio Carlucho, Arrasy Rahman, Eliott Fosong, William Macke, Mohan Sridharan, Peter Stone, and Stefano Albrecht, In The 19th European Conference on Multi-Agent Systems (EUMAS), Dusseldorf, Germany, September 2022.
Adapting to Unseen Driving Conditions Using Context-Aware Neural Networks 2022
Suhaib Abdulquddos, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
Adversarial Imitation Learning from Video using a State Observer 2022
Haresh Karnan, Garrett Warnell, Faraz Torabi, and Peter Stone, In International Conference on Robotics and Automation, 2022, Philadelphia, Pennsylvania, May 2022.
APPL: Adaptive Planner Parameter Learning 2022
Xuesu Xiao, Zizhao Wang, Zifan Xu, Bo Liu, abd Gauraang Dhamankar, Anirudh Nair, Garrett Warnell, and Peter Stone, Robotics and Autonomous Systems (2022).
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Benchmark Autonomous Robot Navigation Challenge at ICRA 2022 2022
Xuesu Xiao, Zifan Xu, Zizhao Wang, Yunlong Song, Garrett Warnell, Peter Stone, Tingnan Zhang, Shravan Ravi, Gary Wang, Haresh Karnan, Joydeep Biswas, Nicholas Mohammad, Lauren Bramblett, Rahul Peddi, Nicola Bezzo, Zhanteng Xie, and Philip Dames, IEEE Robotics and Automation Magazine (2022).
Biological Underpinnings of Lifelong Learning Machines 2022
D. Kudithipudi, M. Aguilar-Simon, J. Babb, M. Bazhenov, D. Blackiston, J. Bongard, A. P. Brna, S. C. Raja, N. Cheney, J. Clune, A. Daram, S. Fusi, P. Helfer, L. Kay, N. Ketz, Z. Kira, S. Kolouri, J. L. Krichmar, S. Kriegman, M. Levin, S. Madireddy, S. Manicka, A. Marjaninejad, B. McNaughton, R. Miikkulainen, Z. Navratilova, T. Pandit, A. Parker, P. K. Pilly, S. Risi, T. J. Sejnowski, A. Soltoggio, N. Soures, A. S. Tolias, D. Urbina-Melendez, F. J. Valero-Cuevas, G. M. van de Ven, J. T. Vogelstein, F. Wang, R. Weiss, A. Yanguas-Gil, Z. Zou, H. Siegelman, Nature Machine Intelligence, Vol. 4 (2022).
BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach 2022
Bo Liu, Mao Ye, Stephen Wright, Peter Stone, and Qiang Liu, In Conference on Neural Information Processing Systems, 2022, New Orleans, LA, December 2022.
Bottom-Up Skill Discovery from Unsegmented Demonstrations for Long-Horizon Robot Manipulation 2022
Yifeng Zhu, Peter Stone, and Yuke Zhu, IEEE Robotics and Automation Letters (2022).
Calculational proofs 2022
Vladimir Lifschitz, In Edsger Wybe Dijkstra: his Life, Work and Legacy, 2022. Association for Computing Machinery.
Causal Dynamics Learning for Task-Independent State Abstraction 2022
Zizhao Wang, Xuesu Xiao, Zifan Xu, Yuke Zhu, and Peter Stone, In roceedings of the 39th International Conference on Machine Learning (ICML2022), Baltimore, USA, July 2022.
Constructing Individualized Computational Models for Dementia Patients 2022
Peggy Fidelman, Uli Grasemann, Claudia Penaloza, Michael Scimeca, Yakeel T. Quiroz, Swathi Kiran, Risto Miikkulainen, In Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022.
Continual Learning and Private Unlearning 2022
Bo Liu, Qiang Liu, and Peter Stone, In Proceedings of the 1st Conference on Lifelong Learning Agents (CoLLAs), Montreal, Canada, August 2022.
Coopernaut: End-to-End Driving with Cooperative Perception for Networked Vehicles 2022
Jiaxun Cui, Hang Qiu, Dian Chen, Peter Stone, and Yuke Zhu, In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New Orleans, LA, June 2022.
Detecting Misclassification Errors in Neural Networks with a Gaussian Process Model 2022
Xin Qiu and Risto Miikkulainen, In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-2022), 2022. (Also arXiv:2010.02065, which also includes the appendices).
DIAS: A Domain-Independent Alife-Based Problem-Solving System 2022
Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, In Proceedings of the 2022 Conference on Artificial Life, 2022.
Discovering Parametric Activation Functions 2022
Garrett Bingham and Risto Miikkulainen, Neural Networks, Vol. 148 (2022), pp. 48-65.
DynaBARN: Benchmarking Metric Ground Navigation in Dynamic Environments 2022
Anirudh Nair, Fulin Jiang, Kang Hou, Zifan Xu, Shuozhe Li, Xuesu Xiao, and Peter Stone, In Proceedings of the 2022 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), November 2022.
Effective Mutation Rate Adaptation through Group Elite Selection 2022
Akarsh Kumar, Bo Liu, Risto Miikkulainen, and Peter Stone, In Proceedings of the Genetic and Evolutionary Computation Conference, 2022. (also arXiv:2204.04817).
Effective Mutation Rate Adaptation through Group Elite Selection 2022
Akarsh Kumar, Bo Liu, Risto Miikkulainen, and Peter Stone, In Proceedings of the Genetic and Evolutionary Computation Conference, Boston, United States, July 2022.
End-to-End Learning to Follow Language Instructions with Compositional Policies 2022
Vanya Cohen, Geraud Nangue Tasse, Nakul Gopalan, Steven James, Ray Mooney, Benjamin Rosman, Workshop on Language and Robot Learning at CoRL 2022 (2022).
Entity-Focused Dense Passage Retrieval for Outside-Knowledge Visual Question Answering 2022
Jialin Wu, Raymond Mooney, In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), December 2022.
Facilitating Software Evolution through Natural Language Comments and Dialogue 2022
Sheena Panthaplackel, PhD Thesis, Department of Computer Science, UT Austin.
How the Brain Dynamically Constructs Sentence-Level Meanings From Word-Level Features 2022
Nora Aguirre-Celis and Risto Miikkulainen, Frontiers in Artificial Intelligence (2022).
Impact of Evaluation Methodologies on Code Summarization 2022
Pengyu Nie, Jiyang Zhang, Junyi Jessy Li, Raymond J. Mooney, and Milos Gligoric, In Annual Meeting of the Association for Computational Linguistics, May 2022.
Incorporating External Information for Visual Question Answering 2022
Jialin Wu, PhD Thesis, Department of Computer Science, UT Austin.
Learning a Robust Multiagent Driving Policy for Traffic Congestion Reduction 2022
Yulin Zhang, William Macke, Jiaxun Cui, Daniel Urieli, and Peter Stone, In Proceedings of the Adaptive and Learning Agents Workshop (ALA), Auckland, NZ, May 2022.
Learning to Correct Mistakes: Backjumping in Long-Horizon Task and Motion Planning 2022
Yoonchang Sung, Zizhao Wang, and Peter Stone, In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), Auckland, New Zealand, December 2022.
Learning to Describe Solutions for Bug Reports Based on Developer Discussions 2022
Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric, Raymond J. Mooney, In Findings of the Annual Meeting of the Association for Computational Linguistics (ACL), May 2022.
Model-Based Meta Automatic Curriculum Learning 2022
Zifan Xu, Yulin Zhang, Shahaf S. Shperberg, Reuth Mirsky, Yulin Zhan, Yuqian Jiang, Bo Liu, and Peter Stone, In Decision Awareness in Reinforcement Learning (DARL) workshop t the +39th International Conference on Machine Learning (ICML), Baltimore, Maryland, USA, July 2022.
Motion Planning and Control for Mobile Robot Navigation Using Machine Learning: a Survey 2022
Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone, Autonomous Robots (2022).
Multi-Modal Answer Validation for Knowledge-Based VQA 2022
Jialin Wu, Jiasen Lu, Ashish Sabharwal, Roozbeh Mottaghi, Proceedings of the AAAI Conference on Artificial Intelligence (2022).
Neuroevolution 2022
Risto Miikkulainen, To Appear In Encyclopedia of Machine Learning and Data Science, 3rd Edition, Dinh Phung, Claude Sammut and Geoffrey I. Webb (Eds.), New York, 2022. Springer.
Planning with Large Language Models via Corrective Re-prompting 2022
Shreyas Sundara Raman, Vanya Cohen, Eric Rosen, Ifrah Idrees, David Paulius, Stefanie Tellex, Foundation Models for Decision Making Workshop at NeurIPS 2022 (2022).
Positive Dependency Graphs Revisited 2022
Jorge Fandinno and Vladimir Lifschitz, Theory and Practice of Logic Programming (2022).
Quantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System 2022
Keya Ghonasgi, Reuth Mirsky, Adrian M Haith, Peter Stone, and Ashish D Deshpande, In Proceedings of the 35th International Conference on Intelligent Robots and Systems (IROS), Kyoto, Japan, October 2022.
Quantifying Human Rationality in Ad-hoc Teamwork 2022
Yair Hanina, Reuth Mirsky, William Macke, and Peter Stone, In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), Online, May 2022.
Quantifying Human Rationality in Ad-hoc Teamwork 2022
Yair Hanina, Reuth Mirsky, William Macke, and Peter Stone, In AAMAS workshop on Autonomous Robots and Multirobot Systems (ARMS), Online, May 2022.
Real-world challenges for multi-agent reinforcement learning in grid-interactive buildings 2022
Kingsley Nweye, Bo Liu, Nagy Zoltan, and Peter Stone, Journal of Energy and AI, 2022 (2022).
Simple Genetic Operators are Universal Approximators of Probability Distributions (and other Advantages of Expressive Encodings) 2022
Elliot Meyerson, Xin Qiu, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 739--748, 2022.
Socially CompliAnt Navigation Dataset (SCAND): A Large-Scale Dataset Of Demonstrations For Social Navigation 2022
Haresh Karnan, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Soren Pirk, Alexander Toshev, Justin Hart, Joydeep Biswas, and Peter Stone, Robotics and Automation Letters (RA-L), 2022 (2022).
Strong Equivalence of Logic Programs with Counting 2022
Vladimir Lifschitz, Theory and Practice of Logic Programming, Vol. 22 (2022).
Task Factorization in Curriculum Learning 2022
Reuth Mirsky, Shahaf S. Shperberg, Yulin Zhang, Zifan Xu, Yuqian Jiang, Jiaxun Cui, and Peter Stone, In Decision Awareness in Reinforcement Learning (DARL) workshop t the 39th International Conference on Machine Learning (ICML), Baltimore, Maryland, USA, July 2022.
Towards a Real-Time, Low-Resource, End-to-end Object Detection Pipeline for Robot Soccer 2022
Sai Kiran Narayanaswami, Mauricio Tec, Ishan Durugkar, Siddharth Desai, Bharath Masetty, Sanmit Narvekar, and Peter Stone, In Proceedings of the RoboCup Symposium, 2022, Bangkok, Thailand, July 2022.
Towards Automated Error Analysis: Learning to Characterize Errors 2022
Tong Gao, Shivang Singh, Raymond J. Mooney, Short version appears in the 19th International Florida Artificial Intelligence Research Society Conference (FLAIRS) (2022).
Translating Definitions into the Language of Logic Programming: A Case Study 2022
Vladimir Lifschitz, In Proceedings of ICLP Workshops, 2022.
Updated Headline Generation: Creating Updated Summaries for Evolving News Stories 2022
Sheena Panthaplackel, Adrian Benton, Mark Dredze, In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, May 2022.
Using Commonsense Knowledge to Answer Why-Questions 2022
Yash Kumar Lal, Niket Tandon, Tanvi Aggarwal, Horace Liu, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian, In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, December 2022.
Using Developer Discussions to Guide Fixing Bugs in Software 2022
Sheena Panthaplackel, Milos Gligoric, Junyi Jessy Li, Raymond J. Mooney, In Findings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), December 2022.
Using Natural Language to Aid Task Specification in Sequential Decision Making Problems 2022
Prasoon Goyal, PhD Thesis, Department of Computer Science, UT Austin.
VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics 2022
Haresh Karnan, Kavan Sikand, Pranav Atreya, Sadegh Rabiee, Xuesu Xiao, Garrett Warnell, Peter Stone, and Joydeep Biswas, In International Conference on Intelligent Robots and Systems, 2022, Kyoto, Japan, October 2022.
VIOLA: Imitation Learning for Vision-Based Manipulation with Object Proposal Priors 2022
Yifeng Zhu, Abhishek Joshi, Peter Stone, and Yuke Zhu, In Proceedings of the 6th Conference on Robot Learning (CoRL 2022), Auckland, New Zealand, January 2022.
VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigation 2022
Haresh Karnan, Garrett Warnell, Xuesu Xiao, and Peter Stone, In International Conference on Robotics and Automation, 2022, Philadelphia, Pennsylvania, May 2022.
Zero-shot Video Moment Retrieval With Off-the-Shelf Models 2022
Anuj Diwan, Puyuan Peng, Raymond J. Mooney, In Workshop on Transfer Learning for Natural Language Processing at NeurIPS 2022, December 2022.
A Biological Perspective on Evolutionary Computation 2021
Risto Miikkulainen and Stephanie Forrest, Nature Machine Intelligence, Vol. 3 (2021), pp. 9-15.
A Lifelong Learning Approach to Mobile Robot Navigation 2021
Bo Liu, Xuesu Xiao, and Peter Stone, In IEEE International Conference on Robotics and Automation (ICRA), 2021, Xi'an, China, June 2021.
A Recap of Early Work onTheory and Knowledge Refinement 2021
Raymond J. Mooney, Jude W. Shavlik, In AAAI Spring Symposium on Combining Machine Learning and Knowledge Engineering, March 2021.
A Scavenger Hunt for Service Robots 2021
Harel Yedidsion, Jennifer Suriadinata, Zifan Xu, Stefan Debruyn, and Peter Stone, In Proceedings of the 2021 International Conference on Robotics and Automation (ICRA 2021), Xi'an China, May 2021.
A Tribute to Edsger Dijkstra 2021
Vladimir Lifschitz, unpublished.
Adversarial Intrinsic Motivation for Reinforcement Learning 2021
Ishan Durugkar, Mauricio Tec, Scott Niekum, and Peter Stone, In Proceedings of the 35th International Conference on Neural Information Processing Systems (NeurIPS 2021), Sydney, Australia, December 2021.
Agile Robot Navigation through Hallucinated Learning and Sober Deployment 2021
Xuesu Xiao, Bo Liu, and Peter Stone, In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, June 2021.
APPLE: Adaptive Planner Parameter Learning From Evaluative Feedback 2021
Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone, {IEEE} Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems ({IROS}) (2021).
APPLI: Adaptive Planner Parameter Learning From Interventions 2021
Zizhao Wang, Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone, In Proceedings of the International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 2021.
APPLR: Adaptive Planner Parameter Learning from Reinforcement 2021
Zifan Xu, Gauraang Dhamankar, Anirudh Nair, Xuesu Xiao, Garrett Warnell, Bo Liu, Zizhao Wang, and Peter Stone, In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, June 2021.
Capturing Skill State in Curriculum Learning for Human Skill Acquisition 2021
Keya Ghonasgi, Reuth Mirsky, Sanmit Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone, and Ashish D. Deshpande, In International Conference on Intelligent Robots and Systems (IROS), Virtual, September 2021.
Coach-Player Multi-Agent Reinforcement Learning for Dynamic Team Composition 2021
Bo Liu, Qiang Liu, Peter Stone, Animesh Garg, Yuke Zhu, and Animashree Anandkumar, In Proceedings of the 38th International Conference on Machine Learning, PMLR 139, 2021 (ICML), Vienna, Austria, July 2021.
Conflict-Averse Gradient Descent for Multi-task learning 2021
Bo Liu, Xingchao Liu, Xiaojie Jin, Peter Stone, and Qiang Liu, In Conference on Neural Information Processing Systems, 2021, Virtual, December 2021.
Copy That! Editing Sequences by Copying Spans 2021
Sheena Panthaplackel, Miltiadis Allamanis, Marc Brockschmidt, In The AAAI Conference on Artificial Intelligence (AAAI), February 2021.
Creative AI through Evolutionary Computation: Principles and Examples 2021
Risto Miikkulainen, SN Computer Science, Vol. 2 (2021), pp. 163.
DEALIO: Data-Efficient Adversarial Learning for Imitation from Observation 2021
Faraz Torabi, Garrett Warnell, and Peter Stone, In Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic, September 2021.
Deep Just-In-Time Inconsistency Detection Between Comments and Source Code 2021
Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric, Raymond J. Mooney, In The AAAI Conference on Artificial Intelligence (AAAI), Vol. arXiv:2010.01625, February 2021.
Dialog Policy Learning for Joint Clarification and Active Learning Queries 2021
Aishwarya Padmakumar, Raymond J. Mooney, In The AAAI Conference on Artificial Intelligence (AAAI), Vol. , February 2021.
Effective Regularization Through Loss-Function Metalearning 2021
Santiago Gonzalez and Risto Miikkulainen, arXiv:2010.00788 (2021).
Evaluating Medical Aesthetics Treatments through Evolved Age-Estimation Models 2021
Risto Miikkulainen, Elliot Meyerson, Xin Qiu, Ujjayant Sinha, Raghav Kumar, Karen Hofmann, Yiyang Matt Yan, Michael Ye, Jingyuan Yang, Damon Caiazza, and Stephanie Manson Brown, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1009–1017, 2021.
Expected Value of Communication for Planning in Ad Hoc Teamwork 2021
William Macke, Reuth Mirsky, and Peter Stone, In Proceedings of the 35th Conference on Artificial Intelligence (AAAI), February 2021.
Facilitating Software Evolution through Natural Language Comments and Dialogue 2021
Sheena Panthaplackel, Ph.D. Proposal.
From Agile Ground to Aerial Navigation: Learning from Learned Hallucination 2021
Zizhao Wang, Xuesu Xiao, Alexander J Nettekoven, Kadhiravan Umasankar, Anika Singh, Sriram Bommakanti, Ufuk Topcu, and Peter Stone, In Proceedings of the International Conference on Intelligent Robots and Systems (IROS 2021), Prague, Czech Republic, October 2021.
From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic 2021
Risto Miikkulainen, Olivier Francon, Elliot Meyerson, Xin Qiu, Darren Sargent, Elisa Canzani, Babak Hodjat, To Appear In IEEE Transactions on Evolutionary Computation, Vol. 25 (2021), pp. 386-401.
From Words to Sentences and Back: Characterizing Context-dependent Meaning Representations in the Brain 2021
Nora Aguirre-Celis a.k.a. Nora E. Aguirre Sampayo, PhD Thesis, Instituto Tecnologico y de Estudios Superiores de Monterrey.
Generalization of Agent Behavior through Explicit Representation of Context 2021
Cem Tutum, Suhaib Abdulquddos, Risto Miikkulainen, In Proceedings of the 3rd IEEE Conference on Games, , 2021.
Goal Blending for Responsive Shared Autonomy in a Navigating Vehicle 2021
Yu-Sian Jiang, Garrett Warnell, and Peter Stone, In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), A Virtual Conference, February 2021.
Grounded Action Transformation for Sim-to-Real Reinforcement Learning 2021
Josiah P.Hanna, Siddharth Desai, Haresh Karnan, Garrett Warnell, and Peter Stone, Special Issue on Reinforcement Learning for Real Life, Machine Learning, 2021 (2021).
Here and There with Arithmetic 2021
Vladimir Lifschitz, Theory and Practice of Logic Programming, Vol. 21 (2021).
Importance Sampling in Reinforcement Learning with an Estimated Behavior Policy 2021
Josiah P. Hanna, Scott Niekum, and Peter Stone, Machine Learning (MLJ), Vol. 110, 6 (2021), pp. 1267–1317.
Improving Neural Network Learning Through Dual Variable Learning Rates 2021
Elizabeth Liner, Risto Miikkulainen, In Proceedings of the International Joint Conference on Neural Networks, 2021.
Improving VQA and its Explanations by Comparing Competing Explanations 2021
Jialin Wu, Liyan Chen, Raymond J. Mooney, In The AAAI Conference on Artificial Intelligence (AAAI), Explainable Agency in Artificial Intelligence Workshop, Vol. arXiv:2006.15631, February 2021.
Incorporating Textual Resources to Improve Visual Question Answering 2021
Jialin Wu, Ph.D. Proposal.
Incorpotating Gaze into Social Navigation 2021
Justin Hart, Reuth Mirsky, Xuesu Xiao, and Peter Stone, In Robotics: Science and Systems Workshop on Social Robot Navigation (RSS), Virtual, July 2021.
Intelligent Disobedience and AI Rebel Agents in Assistive Robotics 2021
Reuth Mirsky and Peter Stone, In ASIMOV workshop as part of the International Conference on Intelligent Robots and Systems (IROS), Virtual, November 2021.
Is the Cerebellum a Model-Based Reinforcement Learning Agent? 2021
Bharath Masetty, Reuth Mirsky, Ashish D. Deshpande, Michael Mauk, and Peter Stone, In Adaptive and Learning Agents Workshop at AAMAS, Virtual, May 2021.
Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain 2021
Xuesu Xiao, Joydeep Biswas, and Peter Stone, In Opportunities and Challenges with Autonomous Racing Workshop at the 2021 IEEE International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, June 2021.
Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain 2021
Xuesu Xiao, Joydeep Biswas, and Peter Stone, IEEE Robotics and Automation Letters (2021).
Lucid Dreaming for Experience Replay: Refreshing Past States with the Current Policy 2021
Yunshu Du, Garrett Warnell, Assefaw Gebremedhin, Peter Stone, and Matthew E. Taylor, Neural Computing and Applications (2021).
Machine Learning Methods for Local Motion Planning: A Study of End-to-End vs. Parameter Learning 2021
Zifan Xu, Xuesu Xiao, Garrett Warnell, Anirudh Nair, and Peter Stone, In Proceedings of the 2021 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2021), New York, USA, October 2021.
Machine versus Human Attention in Deep Reinforcement Learning Tasks 2021
Sihang Guo, Ruohan Zhang, Bo Liu, Yifeng Zhu, Mary Hayhoe, Dana Ballard, and Peter Stone, In Conference on Neural Information Processing Systems, 2021, Virtual, December 2021.
Multiagent Epidemiologic Inference through Realtime Contact Tracing 2021
Guni Sharon, James Ault, Peter Stone, Varun Kompella, and Roberto Capobianco, In Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2021), London, UK, May 2021.
Neuroevolution: A Synergy of Evolution and Learning 2021
Risto Miikkulainen, Plenary presentation at the Congress for Evolutionary Computation (CEC'21).
Optimizing Loss Functions Through Multivariate Taylor Polynomial Parameterization 2021
Santiago Gonzalez and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 305-313, 2021.
Predicting language treatment response in bilingual aphasia using neural network-based patient models 2021
Uli Grasemann, Claudia Peñaloza, Maria Dekhtyar, Risto Miikkulainen, and Swathi Kiran , Scientific Reports, Vol. 11, 10497 (2021), pp. 1-11.
RAIL: A modular framework for Reinforcement-learning-based Adversarial Imitation Learning 2021
Eddy Hudson, Garrett Warnell, and Peter Stone, In Autonomous Robots and Multirobot Systems Workshop at the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), London, UK, May 2021.
Reasoning about Human Behavior in Ad Hoc Teamwork 2021
Jennifer Suriadinata, William Macke, Reuth Mirsky, and Peter Stone, In Adaptive and learning Agents Workshop at AAMAS 2021, May 2021.
Recent Advances in Leveraging Human Guidance for Sequential Decision-Making Tasks 2021
Ruohan Zhang, Faraz Torabi, Garrett Warnell, and Peter Stone, Autonomous Agents and Multi-Agent Systems (2021).
Regularized Evolutionary Population-Based Training 2021
Jason Liang, Santiago Gonzalez, Hormoz Shahrzad, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 323-331, 2021.
Scalable Multiagent Driving Policies For Reducing Traffic Congestion 2021
Jiaxun Cui, William Macke, Harel Yedidsion, Aastha Goyal, Daniel Urieli, and Peter Stone, No other information
Supervised Attention from Natural Language Feedback for Reinforcement Learning 2021
Clara Cecilia Cannon, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
Team Orienteering Coverage Planning with Uncertain Reward 2021
Bo Liu, Xuesu Xiao, and Peter Stone, No other information
TellMeWhy: A Dataset for Answering Why-Questions in Narratives 2021
Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian, In Findings of ACL 2021, August 2021.
Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks 2021
Yuqian Jiang, Suda Bharadwaj, Bo Wu, Rishi Shah, Ufuk Topcu, and Peter Stone, In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), Virtual Conference, February 2021.
The Seeing-Eye Robot Grand Challenge: Rethinking Automated Care 2021
Reuth Mirsky and Peter Stone, In Proceedings of the 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021), Online, May 2021.
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings 2021
Elliot Meyerson and Risto Miikkulainen, To Appear In International Conference on Learning Representations, 2021.
Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination 2021
Xuesu Xiao, Bo Liu, Garrett Warnell, and Peter Stone, IEEE Robotics and Automation Letters (2021).
Transforming Gringo Rules into Formulas in a Natural Way 2021
Vladimir Lifschitz, In Proceedings of European Conference on Logics in Artificial Intelligence, 2021.
Understanding the Semantic Space: How Word Meanings Dynamically Adapt in the Context of a Sentence 2021
Nora Aguirre-Celis and Risto Miikkulainen, In Proceedings of the Workshop on Semantic Spaces at the Intersection of NLP, Physics, and Cognitive Science , Groningen, Netherlands, June 2021.
Using Natural Language to Aid Task Specification in Sequential Decision Making Problems 2021
Prasoon Goyal, Ph.D. Proposal.
Watch Where You're Going! Gaze and Head Orientation as Predictors for Social Robot Navigation 2021
Blake Holman, Abrar Anwar, Akash Singh, Mauricio Tec, Justin Hart, and Peter Stone, In Proceedings of the International Conference on Robotics and Automation (ICRA 2021), Xi'an, China, May 2021.
Zero-shot Task Adaptation using Natural Language 2021
Prasoon Goyal, Raymond J. Mooney, Scott Niekum, Arxiv (2021).
A Comparison of the Taguchi Method and Evolutionary Optimization in Multivariate Testing 2020
Jingbo Jiang, Diego Legrand, Robert Severn, and Risto Miikkulainen, In Proceedings of the 2020 IEEE Congress on Evolutionary Computation, 2020.
A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork 2020
Reuth Mirsky, William Macke, Andy Wang, Harel Yedidsion, and Peter Stone, In Proceedings of the 29th International Joint Conference on Artificial Intelligence, Yokohama, Japan, January 2020.
Adapting to Unseen Environments through Explicit Representation of Context 2020
Cem C Tutum, Risto Miikkulainen, In Proceedings of the 2020 Conference on Artificial Life (ALIFE 2020), pp. 581--588, Montreal, Canada, July 2020. The MIT Press.
Agents teaching agents: a survey on inter-agent transfer learning 2020
Felipe Leno Da Silva, Garrett Warnell, Anna Helena Reali Costa, and Peter Stone, Autonomous Agents and Multi-Agent Systems (2020).
An Imitation from Observation Approach to Transfer Learning with Dynamics Mismatch 2020
Siddarth Desai, Ishan Durugkar, Haresh Karnan, Garrett Warnell, Josiah Hanna, and Peter Stone, In Proceedings of the 34th International Conference on Neural Information Processing Systems (NeurIPS 2020), Virtual, December 2020.
APPLD: Adaptive Planner Parameter Learning from Demonstration 2020
Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, and Peter Stone, No other information
Ascend by Evolv: AI-Based Massively Multivariate Conversion Rate Optimization 2020
Risto Miikkulainen, Myles Brundage, Jonathan Epstein, Tyler Foster, Babak Hodjat, Neil Iscoe, Jingbo Jiang, Diego Legrand, Sam Nazari, Xin Qiu, Michael Scharff, Cory Schoolland, Robert Severn, Aaron Shagrin, AI Magazine, Vol. 41 (2020), pp. 44-60.
Associating Natural Language Comment and Source Code Entities 2020
Sheena Panthaplackel, Milos Gligoric, Raymond J. Mooney and Junyi Jessy Li, In The AAAI Conference on Artificial Intelligence (AAAI), February 2020.
Balancing Individual Preferences and Shared Objectives in Multiagent Reinforcement Learning 2020
Ishan Durugkar, Elad Liebman, and Peter Stone, Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020) (2020).
Benchmarking Metric Ground Navigation 2020
Daniel Perille, Abigail Truong, Xuesu Xiao, and Peter Stone, In Proceedings of the 2020 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR 2016), Virtual Conference, November 2020.
Characterizing Dynamic Word Meaning Representations in the Brain 2020
Nora Aguirre-Celis and Risto Miikkulainen, In Proceedings of the 6th Workshop on Cognitive Aspects of the Lexicon (CogALex-VI), Barcelona, ES, December 2020.
Characterizing the Effect of Sentence Context on Word Meanings: Mapping Brain to Behavior 2020
Nora Aguirre-Celis and Risto Miikkulainen, arXiv:2007.13840 (2020).
Creative AI Through Evolutionary Computation 2020
Risto Miikkulainen, To Appear In Evolution in Action: Past, Present and Future, Banzhaf et al. (Eds.), New York 2020. Springer.
Deep R-Learning for Continual Area Sweeping 2020
Rishi Shah, Yuqian Jiang, Justin Hart, and Peter Stone, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020) (2020).
Dialog as a Vehicle for Lifelong Learning 2020
Aishwarya Padmakumar, Raymond J. Mooney, In Position Paper Track at the SIGDIAL Special Session on Physically Situated Dialogue (RoboDial 2.0), July 2020.
Dialog as a Vehicle for Lifelong Learning of Grounded Language Understanding Systems 2020
Aishwarya Padmakumar, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription 2020
Olivier Francon, Santiago Gonzalez, Babak Hodjat, Elliot Meyerson, Risto Miikkulainen, Xin Qiu, Hormoz Shahrzad, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2020), 2020.
Enhanced Optimization with Composite Objectives and Novelty Pulsation 2020
Hormoz Shahrzad, Babak Hodjat, Camille Dolle, Andrei Denissov, Simon Lau, Donn Goodhew, Justin Dyer, and Risto Miikkulainen, To Appear In Genetic Programming Theory and Practice XVII 2020. Springer, New York.
Evaluating the Robustness of Natural Language Reward Shaping Models to Spatial Relations 2020
Antony Yun, Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
Evolution of Complex Coordinated Behavior 2020
Padmini Rajagopalan, Kay E. Holekamp and Risto Miikkulainen, In 2020 IEEE Congress on Evolutionary Computation (CEC), July 2020.
Evolutionary Optimization of Deep Learning Activation Functions 2020
Garrett Bingham, William Macke, and Risto Miikkulainen, In Genetic and Evolutionary Computation Conference (GECCO '20), pp. 289-296, Cancun, Mexico, 2020.
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks 2020
Lemeng Wu, Bo Liu, Peter Stone, and Qiang Liu, In Advances in Neural Information Processing Systems 34 (2020), Vancouver, Canada, December 2020.
From Nodes to Networks: Evolving Recurrent Neural Networks 2020
Aditya Rawal, Risto Miikkulainen, In Deep Neural Evolution: Deep Learning with Evolutionary Computation, H. Iba and N. Noman (Eds.), pp. 233-251 2020. Springer. (also arxiv:1803.04439).
Improved Training Speed, Accuracy, and Data Utilization Through Loss Function Optimization 2020
Santiago Gonzalez and Risto Miikkulainen, In Proceedings of the 2020 IEEE Congress on Evolutionary Computation (CEC), pp. 1-8, July 2020.
Improving Deep Learning Through Loss-Function Evolution 2020
Santiago Gonzalez, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog 2020
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, Raymond J. Mooney, The Journal of Artificial Intelligence Research (JAIR), Vol. 67 (2020), pp. 327-374.
Learning to Improve Multi-Robot Hallway Navigation 2020
Jin-Soo Park, Brian Tsang, Harel Yedidsion, Garrett Warnell, Daehyun Kyoung, and Peter Stone, In Proceedings of the 4th Conference on Robot Learning (CoRL), Virtual Conference, November 2020.
Learning to Update Natural Language Comments Based on Code Changes 2020
Sheena Panthaplackel, Pengyu Nie, Milos Gligoric, Junyi Jessy Li, and Raymond J. Mooney, In Proceedings of the 58th Annual Conference of the Association for Computational Linguistics (ACL), July 2020.
MDEA: Malware Detection with Evolutionary Adversarial Learning 2020
Xiruo Wang, Risto Miikkulainen, In Proceedings of the 2020 IEEE Congress on Evolutionary Computation, 2020.
On Sampling Error in Batch Action-Value Prediction Algorithms 2020
Brahma S. Pavse, Josiah P. Hanna, Ishan Durugkar, and Peter Stone, In In the Offline Reinforcement Learning Workshop at Neural Information Processing Systems (NeurIPS), December 2020., Remote (Virtual Conference), December 2020.
PixL2R: Guiding Reinforcement Learning using Natural Language by Mapping Pixels to Rewards 2020
Prasoon Goyal, Scott Niekum, Raymond J. Mooney, In 4th Conference on Robot Learning (CoRL), November 2020. Also presented on the 1st Language in Reinforcement Learning (LaReL) Workshop at ICML, July 2020 (Best Paper Award), the 6th Deep Rein...
Policy Evaluation in Continuous MDPs with Efficient Kernelized Gradient Temporal Difference 2020
Alec Koppel, Garrett Warnell, Ethan Stump, Peter Stone, and Alejandro Ribeiro, No other information
Quantifying Point-Prediction Uncertainty in Neural Networks via Residual Estimation with an I/O Kernel 2020
Xin Qiu, Elliot Meyerson, Risto Miikkulainen, In International Conference on Learning Representations, 2020.
Reducing Sampling Error in Batch Temporal Difference Learning 2020
Brahma Pavse, Ishan Durugkar, Josiah Hanna, and Peter Stone, In Proceedings of the 37th International Conference on Machine Learning (ICML), Vienna, Austria (Virtual Conference), July 2020.
Reinforced Grounded Action Transformation for Sim-to-Real Transfer 2020
Haresh Karnan, Siddharth Desai, Josiah P. Hanna, Garrett Warnell, and Peter Stone, In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), October 2020.
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration 2020
Brahma Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone, IEEE Robotics and Automation Letters, presented at International Conference on Intelligent Robots and Systems (IROS) (2020).
Stochastic Grounded Action Transformation for Robot Learning in Simulation 2020
Siddharth Desai, Haresh Karnan, Josiah P. Hanna, Garrett Warnell, and Peter Stone, In IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS 2020), Las Vegas, NV, USA, October 2020.
Systematic Generalization on gSCAN with Language Conditioned Embedding 2020
Tong Gao, Qi Huang and Raymond J. Mooney, In The 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing , December 2020.
Test pub 2020
Test100, asd, Vol. asd, 1 (2020), pp. asd.
The EMPATHIC Framework for Task Learning from Implicit Human Feedback 2020
Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, and W. Bradley Knox, In Proceedings of the 4th Conference on Robot Learning (CoRL 2020), Cambridge MA, USA, November 2020.
The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation 2020
Shih-Yun Lo, Shiqi Zhang, and Peter Stone, The Journal of Artificial Intelligence Research (JAIR), Vol. 67 (2020).
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings 2020
Elliot Meyerson and Risto Miikkulainen, arxiv:2010.02354 (2020).
Towards Verifying Logic Programs in the Input Language of clingo 2020
Vladimir Lifschitz, Patrick Lühne, and Torsten Schaub, In Fields of Logic and Computation III, Essays Dedicated to Yuri Gurevich on the Occasion of His 80th Birthday, pp. 190-209, 2020. Springer.
Using Human-Inspired Signals to Disambiguate Navigational Intentions 2020
Justin Hart, Reuth Mirsky, Xuesu Xiao, Stone Tejeda, Bonny Mahajan, Jamin Goo, Kathryn Baldauf, Sydney Owen, and Peter Stone, In Proceedings of the 12th International Conference on Social Robotics (ICSR), Golden, Colorado, November 2020.
Verifying Tight Logic Programs with anthem and vampire 2020
Jorge Fandinno, Vladimir Lifschitz, Patrick Lühne, Torsten Schaub, Theory and Practice of Logic Programming, Vol. 20, 5 (2020), pp. 735--750.
Designing Neural Networks through Evolutionary Algorithms 2019
Kenneth O. Stanley, Jeff Clune, Joel Lehman, and Risto Miikkulainen, Nature Machine Intelligence, Vol. 1 (2019), pp. 24–35.
A Framework for Writing Trigger - Action Todo Comments in Executable Format 2019
Pengyu Nie, Rishabh Rai, Junyi Jessy Li, Sarfraz Khurshid, Raymond J. Mooney, Milos Gligoric, In Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE), Tallinn, Estonia, August 2019. Distinguished Paper ...
A kernel Loss for Solving Bellman Equation 2019
Yihao Feng, Lihong Li, Qiang Liu, No other information
Ad hoc Teamwork with Behavior Switching Agents 2019
Manish Ravula, Shani Alkobi, and Peter Stone, International Joint Conference on Artificial Intelligence (IJCAI) (2019).
AInix: An open platform for natural language interfaces to shell commands 2019
David Gros, Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
Better Future through AI: Avoiding Pitfalls and Guiding AI Towards its Full Potential 2019
Risto Miikkulainen, Bret Greenstein, Babak Hodjat, Jerry Smith, arxiv:1905.13178 (2019).
BiLex: A computational approach to the effects of age of acquisition and language exposure on bilingual lexical access 2019
Claudia Peñaloza, Uli Grasemann, Maria Dekhtyar, Risto Miikkulainen, and Swathi Kiran, Brain and Language, Vol. 195, 104643 (2019).
Building Self-Play Curricula Online by Playing with Expert Agents in Adversarial Games 2019
Felipe Leno Da Silva, Anna Helena Reali Costa, and Peter Stone, In Proceedings of the 8th Brazilian Conference on Intelligent Systems (BRACIS), Salvador, Bahia, Brazil, October 2019.
Data Augmentation for Deep Transfer Learning 2019
Cameron R. Wolfe and Keld T. Lundgaard, No other information
Discretization of Game Space by Environment Attributes 2019
Alexander Braylan and Risto Miikkulainen, To Appear In The 2nd Knowledge Extraction from Games Workshop 2019. AAAI.
Do Human Rationales Improve Machine Explanations? 2019
Julia Strout, Ye Zhang, Raymond J. Mooney, In Proceedings of the Second BlackboxNLP Workshop at ACL, pp. 56-62, Florence, Italy, August 2019.
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation 2019
Ziyang Tang*, Yihao Feng*, Lihong Li, Denny Zhou, Qiang Liu , No other information
Enhancing Evolutionary Conversion Rate Optimization via Multi-armed Bandit Algorithms 2019
Xin Qiu and Risto Miikkulainen, In Proceedings of the 31st Conference on Innovative Applications of Artificial Intelligence 2019.
Evolutionary Neural AutoML for Deep Learning 2019
Jason Liang, Elliot Meyerson, Babak Hodjat, Dan Fink, Karl Mutch, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2019), pp. 401–409 2019.
Evolutionary Optimization of Neural-Network Models of Human Behavior 2019
Uli Grasemann, Risto Miikkulainen, Claudia Peñaloza, Maria Dekhtyar, and Swathi Kiran, Proceedings of the International Conference on Cognitive Modeling (2019).
Evolving Deep Neural Networks 2019
Risto Miikkulainen, Jason Liang, Elliot Meyerson, Aditya Rawal, Dan Fink, Olivier Francon, Bala Raju, Hormoz Shahrzad, Arshak Navruzyan, Nigel Duffy, and Babak Hodjat, In Artificial Intelligence in the Age of Neural Networks and Brain Computing, Robert Kozma, Cesare Alippi, Yoonsuck Choe, and Francesco Carlo Morabito (Eds.), pp. 293-312 2019. Amsterdam: Elsev...
Exploration via Hindsight Goal Generation 2019
Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng, No other information
Factors that Affect the Evolution of Complex Cooperative Behavior 2019
Padmini Rajagopalan, Kay E. Holekamp and Risto Miikkulainen, In The 2019 Conference on Artificial Life (ALIFE 2019), pp. 333--340, July 2019.
Faithful Multimodal Explanation for Visual Question Answering 2019
Jialin Wu and Raymond J. Mooney, In Proceedings of the Second BlackboxNLP Workshop at ACL, pp. 103-112, Florence, Italy, August 2019.
Faster Training by Selecting Samples Using Embeddings 2019
Santiago Gonzalez, Joshua Landgraf, and Risto Miikkulainen, Proceedings of the 2019 International Joint Conference on Neural Networks (2019), pp. 1-7.
Flavor-cyber-agriculture: Optimization of plant metabolites in an open-source control environment through surrogate modeling 2019
Arielle J. Johnson, Elliot Meyerson, John de la Parra, Timothy L. Savas, Risto Miikkulainen, Caleb B. Harper, bioRxiv:424226, Vol. (2019).
Functional Generative Design of Mechanisms with Recurrent Neural Networks and Novelty Search 2019
Cameron R. Wolfe, Cem C. Tutum and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019), pp. 7, Prague, Czech Republic, July 2019.
Generating Question Relevant Captions to Aid Visual Question Answering 2019
Jialin Wu, Zeyuan Hu, Raymond J. Mooney, In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics (ACL), Florence, Italy, August 2019.
Generative Adversarial Imitation from Observation 2019
Faraz Torabi, Garrett Warnell, and Peter Stone, Imitation, Intent, and Interaction (I3) Workshop at ICML 2019 (2019).
Hidden State Guidance: Improving Image Captioning using An Image Conditioned Autoencoder 2019
Jialin Wu and Raymond J. Mooney, In Proceedings of the Visually Grounded Interaction and Language Workshop at NeurIPS 2019, December 2019.
Imitation Learning from Video by Leveraging Proprioception 2019
Faraz Torabi, Garrett Warnell, and Peter Stone, In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, August 2019.
Implementing evolutionary optimization to model resting state functional connectivity 2019
Kaitlin Maile, Risto Miikkulainen, and Manish Saggar, In Society for Neuroscience Abstracts, 2019. Society for Neuroscience.
Importance Sampling Policy Evaluation with an Estimated Behavior Policy 2019
Josiah Hanna, Scott Niekum, and Peter Stone, In Proceedings of the 36th International Conference on Machine Learning (ICML), Long Beach, California, U.S.A., June 2019.
Improving Grounded Natural Language Understanding through Human-Robot Dialog 2019
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney, In IEEE International Conference on Robotics and Automation (ICRA), Montreal, Canada, May 2019.
Improving Neural Language Modeling via Adversarial Training 2019
Dilin Wang*, Chengyue Gong*, Qiang Liu, No other information
Learning Curriculum Policies for Reinforcement Learning 2019
Sanmit Narvekar and Peter Stone, In Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Montreal, Canada, May 2019.
Learning Self-Imitating Diverse Policies 2019
Tanmay Gangwani, Qiang Liu, Jian Peng, No other information
LithoROC: Lithography Hotspot Detection with Explicit ROC Optimization 2019
Wei Ye, Yibo Lin, Meng Li, Qiang Liu, David Z Pan, No other information
MDEA: Malware Detection with Evolutionary Adversarial Learning 2019
Xiruo Wang, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
Mixed Precision Neural Architecture Search for Energy Efficient Deep Learning 2019
Chengyue Gong, Zixuan Jiang, Dilin Wang, Yibo Lin, Qiang Liu, David Z Pan, No other information
Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains 2019
Elliot Meyerson and Risto Miikkulainen, In 33rd Conference on Neural Information Processing Systems (NeurIPS 2019), 2019.
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models 2019
Dilin Wang, Qiang Liu, No other information
Object-model transfer in the general video game domain 2019
Alexander Braylan, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin.
Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy 2019
Yuan Xie, Boyi Liu, Qiang Liu, Zhaoran Wang, Yuan Zhou, Jian Peng, No other information
Open-World Reasoning for Service Robots 2019
Yuqian Jiang, Nick Walker, Justin Hart, Peter Stone, In Proceedings of the 29th International Conference on Automated Planning and Scheduling (ICAPS 2019), Berkeley, CA, USA, July 2019.
Optimal Use Of Verbal Instructions For Multi-Robot Human Navigation Guidance 2019
Harel Yedidsion, Jacqueline Deans, Connor Sheehan, Mahathi Chillara, Justin Hart, Peter Stone, and Raymond J. Mooney, In Proceedings of the Eleventh International Conference on Social Robotics, pp. 133-143 2019. Springer.
Quantifying the Conceptual Combination Effect on Word Meanings 2019
Nora Aguirre-Celis and Risto Miikkulainen, In Proceedings of the 41th Annual Meeting of the Cognitive Science Society, Montreal, CA, July 2019.
Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization 2019
Chengyue Gong, Jian Peng, Qiang Liu, No other information
Recent Advances in Imitation Learning from Observation 2019
Faraz Torabi, Garrett Warnell, and Peter Stone, Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI) (2019).
Reducing Sampling Error in Policy Gradient Learning 2019
Josiah Hanna and Peter Stone, In Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Montreal, Canada, May 2019.
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel 2019
Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma, No other information
RIDM: Reinforced Inverse Dynamics Modeling for Learning from a Single Observed Demonstration 2019
Brahma S. Pavse, Faraz Torabi, Josiah Hanna, Garrett Warnell, and Peter Stone, No other information
Sample-efficient Adversarial Imitation Learning from Observation 2019
Faraz Torabi, Garrett Warnell, and Peter Stone, No other information
Selecting Compliant Agents for Opt-in Micro-Tolling 2019
Josiah Hanna, Guni Sharon, Stephen Boyles, and Peter Stone, In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), Honolulu, HI, January 2019.
Self-Critical Reasoning for Robust Visual Question Answering 2019
Jialin Wu and Raymond J. Mooney, In Proceedings of Neural Information Processing Systems (NeurIPS) , December 2019.
Splitting Steepest Descent for Growing Neural Architectures 2019
Qiang Liu, Lemeng Wu and Dilin Wang, Advances in Neural Information Processing Systems (2019), pp. 10655--10665.
Stein Variational Gradient Descent With Matrix-Valued Kernels 2019
Dilin Wang*, Ziyang Tang*, Chandrajit Bajaj, Qiang Liu, No other information
The right music at the right time: adaptive personalized playlists based on sequence modeling 2019
Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone Peter Stone, Management Information Systems Quarterly, Vol. 43, 3 (2019), pp. 765--786.
Tradeoffs in Neuroevolutionary Learning-Based Real-Time Robotic Task Design in the Imprecise Computation Framework 2019
Pei-Chi Huang, Luis Sentis, Joel Lehman, Chien-Liang Fok, Aloysius K. Mok, Risto Miikkulainen, ACM Transactions on Cyber-Physical Systems, Vol. 3 (2019). DOI 0.1145/3178903.
Using Natural Language for Reward Shaping in Reinforcement Learning 2019
Prasoon Goyal, Scott Niekum, Raymond J. Mooney, In Proceedings of the 28th International Joint Conference on Artificial Intelligence, Macao, China, August 2019.
UT Austin Villa: RoboCup 2018 3D Simulation League Champions 2019
Patrick MacAlpine, Faraz Torabi, Brahma Pavse, John Sigmon and Peter Stone, In RoboCup 2018: Robot Soccer World Cup XXII, Dirk Holz and Katie Genter and Maarouf Saad and Oskar von Stryk (Eds.) 2019. Springer.
Verifying Strong Equivalence of Programs in the Input Language of gringo 2019
Vladimir Lifschitz, Patrick Lühne, and Torsten Schaub, In Proceedings of the 15th International Conference on Logic Programming and Non-monotonic Reasoning 2019.
A Neuroevolutionary Approach to Adaptive Multi-agent Teams 2018
Bobby D. Bryant and Risto Miikkulainen, In Foundations of Trusted Autonomy, H. A. Abbass and J. Scholz and D. J. Reid (Eds.), pp. 87-114, New York 2018. Springer.
A Study of Human-Robot Copilot Systems for En-Route Destination Changing 2018
Yu-Sian Jiang, Garrett Warnell, Eduardo Munera, and Peter Stone, In Proceedings of the 27th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN2018), Nanjing, China, August 2018.
anthem: Transforming gringo Programs into First-Order Theories (Preliminary Report) 2018
Vladimir Lifschitz, Patrick Lühne, Torsten Schaub, In Working Notes of the Workshop on Answer Set Programming and Other Computing Paradigms 2018.
Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems 2018
Stefano Albrecht and Peter Stone, Artificial Intelligence, Vol. 258 (2018), pp. 66--95. Elsevier.
Behavioral Cloning from Observation 2018
Faraz Torabi, Garrett Warnell, and Peter Stone, In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), Stockholm, Sweden, July 2018.
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering 2018
Elliot Meyerson and Risto Miikkulainen, In Proceedings of the Sixth International Conference on Learning Representations (ICLR), Vancouver, Canada 2018.
Breaking the curse of horizon: Infinite-horizon off-policy estimation 2018
Qiang Liu, Lihong Li, Ziyang Tang, Dengyong Zhou, No other information
Combining fMRI Data and Neural Networks to Quantify Contextual Effects in the Brain 2018
Nora Aguirre-Celis and Risto Miikkulainen, In Brain Informatics. BI 2018. Lectures Notes in Computer Sciences, Shouyi Wang, Vicky Yamamoto, Jianzhong Su, Yang Yang, Eric Jones, Leon Iasemidis, Tom Mitchell (Eds.), Vol. 11309, pp. 129-14...
Continually Improving Grounded Natural Language Understanding through Human-Robot Dialog 2018
Jesse Thomason, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Deep TAMER: Interactive agent shaping in high-dimensional state spaces 2018
Garrett Warnell, Nicholas Waytowich, Vernon Lawhern, and Peter Stone, In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2018.
Deterministic Implementations for Reproducibility in Deep Reinforcement Learning 2018
Prabhat Nagarajan, Garrett Warnell, and Peter Stone, In 2nd Reproducibility in Machine Learning Workshop at ICML 2018, Stockholm, Sweden, July 2018.
Discovering Gated Recurrent Neural Network Architectures 2018
Aditya Rawal, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Discovering Multi-Purpose Modules through Deep Multitask Learning 2018
Elliot Meyerson, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
DyETC: Dynamic Electronic Toll Collection for Traffic Congestion Alleviation 2018
Haipeng Chen, Bo An, Guni Sharon, Josiah Hanna, Peter Stone, Chunyan Miao, and Yeng Chai Soh, In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Louisiana, USA, February 2018.
Dynamic Adaptation and Opponent Exploitation in Computer Poker 2018
Xun Li and Risto Miikkulainen, AAAI-18 Workshop for Imperfect Information Games (2018).
Enhanced Optimization with Composite Objectives and Novelty Selection 2018
Hormoz Shahrzad, Daniel Fink and Risto Miikkulainen, In Proceedings of the 2018 Conference on Artificial Life, Tokyo, Japan 2018.
Evolutionary Architecture Search For Deep Multitask Networks 2018
Jason Liang, Elliot Meyerson, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 466–473, Kyoto, Japan, 2018.
Evolutionary Neural Architecture Search for Deep Learning 2018
Jason Zhi Liang, PhD Thesis, The University of Texas at Austin.
Explainable Improved Ensembling for Natural Language and Vision 2018
Nazneen Rajani, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Functional Generative Design: An Evolutionary Approach to 3D-Printing 2018
Cem C. Tutum, Supawit Chockchowwat, Etienne Vouga and Risto Miikkulainen, To Appear In Proceedings of Genetic and Evolutionary Computation Conference (GECCO 2018), pp. 8, Kyoto, Japan, July 2018.
Generating Animated Videos of Human Activities from Natural Language Descriptions 2018
Angela S. Lin, Lemeng Wu, Rodolfo Corona , Kevin Tai , Qixing Huang , Raymond J. Mooney, In Proceedings of the Visually Grounded Interaction and Language Workshop at NeurIPS 2018, December 2018.
Goodness-of-Fit Testing for Discrete Distributions via Stein Discrepancy 2018
Jiasen Yang, Qiang Liu, Vinayak Rao, Jennifer Neville , No other information
Guiding Exploratory Behaviors for Multi-Modal Grounding of Linguistic Descriptions 2018
Jesse Thomason, Jivko Sinapov, Raymond Mooney, Peter Stone, In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18) , February 2018.
Hierarchical Policy Design for Sample-Efficient Learning of Robot Table Tennis Through Self-Play 2018
Reza Mahjourian, PhD Thesis, University of Texas at Austin.
Improved Models and Queries for Grounded Human-Robot Dialog 2018
Aishwarya Padmakumar, PhD Proposal, Department of Computer Science, The University of Texas At Austin.
Inferring User Intention using Gaze in Vehicles 2018
Yu-Sian Jiang, Garrett Warnell, and Peter Stone, In The 20th ACM International Conference on Multimodal Interaction (ICMI), Boulder, Colorado, October 2018.
Interaction and Autonomy in RoboCup@Home and Building-Wide Intelligence 2018
Justin Hart, Harel Yedidsion, Yuqian Jiang, Nick Walker, Rishi Shah, Jesse Thomason, Aishwarya Padmakumar, Rolando Fernandez, Jivko Sinapov, Raymond Mooney, Peter Stone, In Artificial Intelligence (AI) for Human-Robot Interaction (HRI) symposium, AAAI Fall Symposium Series, Arlington, Virginia, October 2018.
Interview to Kunstliche Intelligenz 2018
Vladimir Lifschitz, Kunstliche Intelligenz (2018).
Joint Image Captioning and Question Answering 2018
Jialin Wu, Zeyuan Hu and Raymond J. Mooney , In VQA Challenge and Visual Dialog Workshop at the 31st IEEE Conference on Computer Vision and Pattern Recognition (CVPR-18) , June 2018.
Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog 2018
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney, In Late-breaking Track at the SIGDIAL Special Session on Physically Situated Dialogue (RoboDIAL-18), Melbourne, Australia, July 2018.
Jointly Improving Parsing and Perception for Natural Language Commands through Human-Robot Dialog 2018
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Nick Walker, Yuqian Jiang, Harel Yedidsion, Justin Hart, Peter Stone, and Raymond J. Mooney, In RSS Workshop on Models and Representations for Natural Human-Robot Communication (MRHRC-18). Robotics: Science and Systems (RSS), June 2018.
Learning a Policy for Opportunistic Active Learning 2018
Aishwarya Padmakumar, Peter Stone, Raymond J. Mooney, In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP-18), Brussels, Belgium, November 2018.
Learning to Explore via Meta-Policy Gradient 2018
Tianbing Xu, Qiang Liu, Liang Zhao, Jian Peng, No other information
Learning Useful Features For Poker 2018
Arjun Nagineni, Technical Report, Department of Computer Sciences, The University of Texas at Austin.
Multi-modal Predicate Identification using Dynamically Learned Robot Controllers 2018
Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, and Peter Stone, In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-18), Stockholm, Sweden, July 2018.
Natural Language Processing and Program Analysis for Supporting Todo Comments as Software Evolves 2018
Pengyu Nie, Junyi Jessy Li, Sarfraz Khurshid, Raymond Mooney, Milos Gligoric, In In Proceedings of the AAAI Workshop on NLP for Software Engineering, February 2018.
Opponent Modeling and Exploitation in Poker Using Evolved Recurrent Neural Networks 2018
Xun Li and Risto Miikkulainen, In Proceedings of The Genetic and Evolutionary Computation Conference (GECCO 2018), Kyoto, Japan, July 2018. ACM.
Opponent Modeling and Exploitation in Poker Using Evolved Recurrent Neural Networks 2018
Xun Li, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin..
Overlapping Layered Learning 2018
Patrick MacAlpine and Peter Stone, Artificial Intelligence, Vol. 254 (2018), pp. 21--43. Elsevier.
Passive Demonstrations of Light-Based Robot Signals for Improved Human Interpretability 2018
Rolando Fernandez, Nathan John, Sean Kirmani, Justin Hart, Jivko Sinapov, and Peter Stone, In Proceedings of the 27th {IEEE} International Symposium on Robot and Human Interactive Communication {(RO-MAN)}, Nanjing, China, August 2018.
PETLON - Planning Efficiently for Task-Level Optimal Navigation 2018
Shih-Yun Lo, Shiqi Zhang, and Peter Stone, In Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Stockholm, Sweden, July 2018.
PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification 2018
Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, and Chris Holmes, In Genetic Programming Theory and Practice XIV, New York 2018. Springer.
PRISM: Pose Registration for Integrated Semantic Mapping 2018
Justin W. Hart, Rishi Shah, Sean Kirmani, Nick Walker, Kathryn Baldauf, Nathan John, and Peter Stone, In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, October 2018.
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing---and Back 2018
Elliot Meyerson, Risto Miikkulainen, In Proceedings of the 35th International Conference on Machine Learning, pp. 739-748 2018.
Relating Two Dialects of Answer Set Programming 2018
Amelia Harrison and Vladimir Lifschitz, In Working Notes of the 17th International Workshop on Non-Monotonic Reasoning 2018.
Sentient Ascend: AI-Based Massively Multivariate Conversion Rate Optimization 2018
R. Miikkulainen, N. Iscoe, A. Shagrin, R. Rapp, S. Nazari, P. McGrath, C. Schoolland, E. Achkar, M. Brundage, J. Miller, J. Epstein, and G. Lamba, In Proceedings of the Thirtieth Innovative Applications of Artificial Intelligence Conference 2018. AAAI.
Stacking With Auxiliary Features for Visual Question Answering 2018
Nazneen Fatema Rajani, Raymond J. Mooney, In Proceedings of the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 2217-2226 2018.
State Abstraction Synthesis for Discrete Models of Continuous Domains 2018
Jacob Menashe and Peter Stone, In Data Efficient Reinforcement Learning Workshop at AAAI Spring Symposium, Stanford, CA, USA, March 2018.
Stein Variational Gradient Descent as Moment Matching 2018
Qiang Liu, Dilin Wang, No other information
Stein Variational Gradient Descent Without Gradient 2018
Jun Han, Qiang Liu, No other information
Stein Variational Message Passing for Continuous Graphical Models 2018
Dilin Wang, Zhe Zeng, Qiang Liu, No other information
Towards a Data Efficient Off-Policy Policy Gradient 2018
Josiah Hanna and Peter Stone, In AAAI Spring Symposium on Data Efficient Reinforcement Learning, Palo Alto, CA, March 2018.
Traffic Optimization For a Mixture of Self-interested and Compliant Agents 2018
Guni Sharon, Michael Albert, Tarun Rambha, Stephen Boyles, and Peter Stone, In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Louisiana, USA, February 2018.
Variational inference with tail-adaptive f-divergence 2018
Dilin Wang, Hao Liu, Qiang Liu, No other information
Variety Wins: Soccer-Playing Robots and Infant Walking 2018
Ori Ossmy, Justine E. Hoch, Patrick MacAlpine, Shohan Hasan, Peter Stone, and Karen E. Adolph, Frontiers in Neurorobotics, Vol. 12 (2018), pp. 19.
A Stitch in Time - Autonomous Model Management via Reinforcement Learning 2018
Elad Liebman, Eric Zavesky, and Peter Stone, In Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Stockholm, Sweden, July 2018.
On the Impact of Music on Decision Making in Cooperative Tasks 2018
Elad Liebman, Corey N. White, and Peter Stone, In 19th International Society for Music Information retrieval Conference (ISMIR), Paris, France, September 2018.
A Probabilistic Re-Formulation of No Free Lunch: Continuous Lunches Are Not Free 2017
Alan J. Lockett and Risto Miikkulainen, Evolutionary Computation, Vol. 25 (2017), pp. 503--528.
A Protocol for Mixed Autonomous and Human-Operated Vehicles at Intersections 2017
Guni Sharon and Peter Stone, In Proceedings of the 2nd International Workshop on Agent-based modeling of urban systems (ABMUS-2017), Sao Paulo, Brazil, May 2017.
Achievements in Answer Set Programming 2017
Vladimir Lifschitz, Theory and Practice of Logic Programming (2017).
Advances in Statistical Script Learning 2017
Karl Pichotta, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Automated Design of Robust Mechanisms 2017
Michael Albert, Vincent Conitzer, and Peter Stone, In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, CA, USA, February 2017.
Automatic Curriculum Graph Generation for Reinforcement Learning Agents 2017
Maxwell Svetlik, Matteo Leonetti, Jivko Sinapov, Rishi Shah, Nick Walker, and Peter Stone, In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, February 2017.
Autonomous Task Sequencing for Customized Curriculum Design in Reinforcement Learning 2017
Sanmit Narvekar, Jivko Sinapov, and Peter Stone, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 2017.
Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation 2017
Josiah Hanna, Peter Stone, and Scott Niekum, In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Sao Paolo, Brazil, May 2017.
BWIBots: A platform for bridging the gap between AI and human--robot interaction research 2017
Piyush Khandelwal, Shiqi Zhang, Jivko Sinapov, Matteo Leonetti, Jesse Thomason, Fangkai Yang, Ilaria Gori, Maxwell Svetlik, Priyanka Khante, Vladimir Lifschitz, J. K. Aggarwal, Raymond Mooney, and Peter Stone, The International Journal of Robotics Research (2017).
Captioning Images with Diverse Objects 2017
Subhashini Venugopalan, Lisa Anne Hendricks, Marcus Rohrbach, Raymond Mooney, Trevor Darrell, and Kate Saenko, In Proceedings of the 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR-17), pp. 5753--5761 2017.
CC-Log: Drastically Reducing Storage Requirements for Robots Using Classification and Compression 2017
Santiago Gonzalez, Vijay Chidambaram, Jivko Sinapov, and Peter Stone, In Proceedings of the 9th USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage '17), Santa Clara, CA, July 2017.
Conversion Rate Optimization through Evolutionary Computation 2017
Risto Miikkulainen, Neil Iscoe, Aaron Shagrin, Ron Cordell, Sam Nazari, Cory Schoolland, Myles Brundage, Jonathan Epstein, Randy Dean, Gurmeet Lamba, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2017, Berlin, Germany) 2017.
Data-Efficient Policy Evaluation Through Behavior Policy Search 2017
Josiah Hanna, Philip Thomas, Peter Stone, and Scott Niekum, In Proceedings of the 34th International Conference on Machine Learning (ICML), Sydney, Australia, August 2017.
Decision mechanisms underlying mood-congruent emotional classification 2017
Corey White, Elad Liebman, and Peter Stone, Cognition and Emotion (2017), pp. 1--10. Taylor and Francis.
Designing Better Playlists with Monte Carlo Tree Search 2017
Elad Liebman, Piyush Khandelwal, Maytal Saar-Tsechansky, and Peter Stone, In PROCEEDINGS OF THE TWENTY-NINTH CONFERENCE ON INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE (IAAI-17), San Francisco, USA, February 2017.
Dialog for Language to Code 2017
Shobhit Chaurasia and Raymond J. Mooney, In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), pp. 175-180, Taipei, Taiwan, November 2017.
Dialog for Natural Language to Code 2017
Shobhit Chaurasia, Masters Thesis, Computer Science Department, University of Texas at Austin.
Discovering Evolutionary Stepping Stones through Behavior Domination 2017
Elliot Meyerson and Risto Miikkulainen, To Appear In Proceedings of The Genetic and Evolutionary Computation Conference (GECCO 2017), Berlin, Germany, July 2017. ACM.
Distributional modeling on a diet: One-shot word learning from text only 2017
Su Wang, Stephen Roller, and Katrin Erk, In In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), Taipei, Taiwan, November 2017.
Dynamically Constructed (PO)MDPs for Adaptive Robot Planning 2017
Shiqi Zhang, Piyush Khandelwal, and Peter Stone, In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, February 2017.
Efficient Sampling for Design Optimization of an SLS Product 2017
Nancy Xu, Cem C. Tutum, In Proceedings of the 28th Annual International Solid Freeform Fabrication Symposium, pp. 12, Austin, TX, August 2017.
Ensembling Visual Explanations for VQA 2017
Nazneen Fatema Rajani, Raymond J. Mooney, In Proceedings of the NIPS 2017 workshop on Visually-Grounded Interaction and Language (ViGIL), December 2017.
Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges 2017
Patrick MacAlpine and Peter Stone, In AAMAS Multiagent Interaction without Prior Coordination (MIPC) Workshop, Sao Paulo, Brazil, May 2017.
Evaluating Ad Hoc Teamwork Performance in Drop-In Player Challenges 2017
Patrick MacAlpine and Peter Stone, In Autonomous Agents and Multiagent Systems, AAMAS 2017 Workshops, Best Papers, Gita Sukthankar and Juan A. Rodriguez-Aguilar (Eds.), pp. 168--186 2017. Springer International Publishing.
Evolutionary Decomposition for 3D Printing 2017
Eric A. Yu, Jin Yeom, Cem C. Tutum, Etienne Vouga, Risto Miikkulainen, To Appear In Proceedings of The Genetic and Evolutionary Computation Conference (GECCO 2017) (Best Paper Award), pp. 8 pages, Berlin, Germany, July 2017.
Evolving Adaptive Poker Players for Effective Opponent Exploitation 2017
Xun Li and Risto Miikkulainen, Technical Reports of the Thirty-first AAAI Conference of Artificial Intelligence (AAAI-17) (2017).
Fast and Precise Black and White Ball Detection for RoboCup Soccer 2017
Jacob Menashe, Josh Kelle, Katie Genter, Josiah Hanna, Elad Liebman, Sanmit Narvekar, Ruohan Zhang, and Peter Stone, In {R}obo{C}up-2017: Robot Soccer World Cup {XXI}, 2017 (Eds.), Nagoya, Japan, July 2017.
First-Order Modular Logic Programs and their Conservative Extensions (Extended Abstract) 2017
Amelia Harrison and Yuliya Lierler, To Appear In Proceedings of the 2017 International Joint Conference on Artificial Intelligence 2017.
Formal Methods for Answer Set Programming 2017
Amelia Harrison, PhD Thesis, University of Texas at Austin. Doctoral Dissertation defended at the University of Texas.
From Words to Sentences & Back: Characterizing Context-dependent Meaning Representations in the Brain 2017
Nora Aguirre-Celis, Manuel Valenzuela, and Risto Miikkulainen, In Proceedings of the 39th Annual Meeting of the Cognitive Science Society, London, UK, July 2017.
Grounded Action Transformation for Robot Learning in Simulation 2017
Josiah Hanna and Peter Stone, In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), San Francisco, CA, February 2017.
Guiding Interaction Behaviors for Multi-modal Grounded Language Learning 2017
Jesse Thomason, Jivko Sinapov, and Raymond J. Mooney, In Proceedings of the Workshop on Language Grounding for Robotics at ACL 2017 (RoboNLP-17), Vancouver, Canada, August 2017.
How to Select a Winner in Evolutionary Optimization? 2017
Risto Miikkulainen, Hormoz Shahrzad, Nigel Duffy, and Phil Long, In Proceedings of the IEEE Symposium Series in Computational Intelligence 2017. IEEE.
Improving Black-box Speech Recognition using Semantic Parsing 2017
Rodolfo Corona, Jesse Thomason, and Raymond J. Mooney, In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), pp. 122-127, Taipei, Taiwan, November 2017.
Infinitary Equilibrium Logic and Strongly Equivalent Logic Programs 2017
Amelia Harrison, Vladimir Lifschitz, David Pearce, and Agustín Valverde, Artificial Intelligence, Vol. 246 (2017).
Integrated Commonsense Reasoning and Probabilistic Planning 2017
Shiqi Zhang and Peter Stone, In Proceedings of 2017 ICAPS Workshop on Planning and Robotics, Pittsburgh, Pennsylvania, June 2017.
Integrated Learning of Dialog Strategies and Semantic Parsing 2017
Aishwarya Padmakumar, Jesse Thomason, and Raymond J. Mooney, In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2017), pp. 547--557, Valencia, Spain, April 2017.
Iterative Human-Aware Mobile Robot Navigation 2017
Shih-Yun Lo, Benito Fernandez, and Peter Stone, In Proceedings of the Human-Centered Robotics workshop of the 13th International Conference on Robotics: Science and System (RSS), Cambridge, MA, USA, July 2017.
Leveraging Commonsense Reasoning and Multimodal Perception for Robot Spoken Dialog Systems 2017
Dongcai Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen, In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, September 2017.
Leveraging Discourse Information Effectively for Authorship Attribution 2017
Elisa Ferracane, Su Wang, and Raymond J. Mooney, In In Proceedings of the 8th International Joint Conference on Natural Language Processing (IJCNLP-17), pp. 584–593, Taipei, Taiwan, November 2017.
Mechanism Design with Unknown Correlated Distributions: Can We Learn Optimal Mechanisms? 2017
Michael Albert, Vincent Conitzer, and Peter Stone, In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems (AAMAS-17), Sau Paulo, Brazil, May 2017.
Multi-Modal Word Synset Induction 2017
Jesse Thomason and Raymond J. Mooney, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), pp. 4116--4122, Melbourne, Australia 2017.
Multi-Robot Human Guidance: Human Experiments and Multiple Concurrent Requests 2017
Piyush Khandelwal and Peter Stone, In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), São Paulo, Brazil, May 2017.
Multirobot Symbolic Planning under Temporal Uncertainty 2017
Shiqi Zhang, Yuqian Jiang, Guni Sharon, and Peter Stone, In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Sytems (AAMAS), Sao Paulo, Brazil, May 2017.
Natural-Language Video Description with Deep Recurrent Neural Networks 2017
Subhashini Venugopalan, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Network-wide adaptive tolling for connected and automated vehicles 2017
Guni Sharon, Michael W. Levin, Josiah P. Hanna, Tarun Rambha, Stephen D. Boyles, and Peter Stone, Transportation Research Part C, Vol. 84 (2017), pp. 142--157.
Opportunistic Active Learning for Grounding Natural Language Descriptions 2017
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov, Justin Hart, Peter Stone, and Raymond J. Mooney, In Proceedings of the 1st Annual Conference on Robot Learning (CoRL-17), Sergey Levine and Vincent Vanhoucke and Ken Goldberg (Eds.), pp. 67--76, Mountain View, California, November 2017. PMLR.
Program Completion in the Input Language of GRINGO 2017
Amelia Harrison, Vladimir Lifschitz, and Dhananjay Raju, Theory and Practice of Logic Programming, Vol. 15 (2017).
Real-time Adaptive Tolling Scheme for Optimized Social Welfare in Traffic Networks 2017
Guni Sharon, Josiah P. Hanna, Tarun Rambha, Michael W. Levin, Michael Albert, Stephen D. Boyles, and Peter Stone, In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-2017), Sao Paulo, Brazil, May 2017.
Reasoning about Hypothetical Agent Behaviours and their Parameters 2017
Stefano Albrecht and Peter Stone, In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-17), Sao Paulo, Brazil, May 2017.
Robot Behavioral Exploration and Multimodal Perception using POMDPs 2017
Shiqi Zhang, Jivko Sinapov, Suhua Wei, and Peter Stone, In Proceedings of 2017 AAAI Spring Symposium on Interactive Multi-Sensory Perception for Embodied Agents, Stanford, CA, March 2017.
Stacking With Auxiliary Features 2017
Nazneen Fatema Rajani and Raymond J. Mooney, In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI-17), pp. 2634-2640, Melbourne, Australia 2017.
TD Learning with Constrained Gradients 2017
Ishan Durugkar and Peter Stone, In Proceedings of the Deep Reinforcement Learning Symposium, NIPS 2017, Long Beach, CA, USA, December 2017.
Using Explanations to Improve Ensembling of Visual Question Answering Systems 2017
Nazneen Fatema Rajani and Raymond J. Mooney, In Proceedings of the IJCAI 2017 Workshop on Explainable Artificial Intelligence (XAI), pp. 43-47, Melbourne, Australia, August 2017.
UT Austin Villa: RoboCup 2017 3D Simulation League Competition and Technical Challenges Champions 2017
Patrick MacAlpine and Peter Stone, In {R}obo{C}up 2017: Robot Soccer World Cup {XXI}, Claude Sammut and Oliver Obst and Flavio Tonidandel and Hidehisa Akyama (Eds.) 2017. Springer.
A Study of Layered Learning Strategies Applied to Individual Behaviors in Robot Soccer 2016
David L. Leottau, Javier Ruiz-del-Solar, Patrick MacAlpine, and Peter Stone, In {R}obo{C}up-2015: Robot Soccer World Cup {XIX}, Luis Almeida and Jianmin Ji and Gerald Steinbauer and Sean Luke (Eds.), Berlin, Germany 2016. Springer Verlag.
A synthesis of automated planning and reinforcement learning for efficient, robust decision-making 2016
Matteo Leonetti, Luca Iocchi, and Peter Stone, Artificial Intelligence, Vol. 241 (2016), pp. 103 - 130.
Ad Hoc Teamwork Behaviors for Influencing a Flock 2016
Katie Genter and Peter Stone, Acta Polytechnica (2016).
Adaptation of Surrogate Tasks for Bipedal Walk Optimization 2016
Patrick MacAlpine, Elad Liebman, and Peter Stone, In GECCO Surrogate-Assisted Evolutionary Optimisation (SAEOpt) Workshop, Denver, Colorado, USA, July 2016.
Adding Influencing Agents to a Flock 2016
Katie Genter and Peter Stone, In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS-16), Singapore, Singapore, May 2016.
An Analysis of Using Semantic Parsing for Speech Recognition 2016
Rodolfo Corona, Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
An MDP-Based Winning Approach to Autonomous Power Trading: Formalization and Empirical Analysis 2016
Daniel Urieli and Peter Stone, In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2016.
Answer Sets and the Language of Answer Set Programming 2016
Vladimir Lifschitz, AI Magazine (2016).
Autonomous Electricity Trading using Time-Of-Use Tariffs in a Competitive Market 2016
Daniel Urieli and Peter Stone, In Proceedings of the 30th Conference on Artificial Intelligence (AAAI 2016), Phoenix, AZ, USA, February 2016.
Combining Supervised and Unsupervised Ensembles for Knowledge Base Population 2016
Nazneen Fatema Rajani and Raymond J. Mooney, To Appear In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16) 2016.
Constructing Game Agents Through Simulated Evolution 2016
Jacob Schrum and Risto Miikkulainen, In Encyclopedia of Computer Graphics and Games, Newton Lee (Eds.), pp. 1--10 2016. Springer.
Continuously Improving Natural Language Understanding for Robotic Systems through Semantic Parsing, Dialog, and Multi-modal Perception 2016
Jesse Thomason, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Deep Compositional Captioning: Describing Novel Object Categories without Paired Training Data 2016
Lisa Anne Hendricks, Subhashini Venugopalan, Marcus Rohrbach, Raymond Mooney, Kate Saenko, and Trevor Darrell, In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR-16), pp. 1--10 2016.
Deep Imitation Learning for Parameterized Action Spaces 2016
Matthew Hausknecht, Yilun Chen, and Peter Stone, In AAMAS Adaptive Learning Agents (ALA) Workshop, Singapore, May 2016.
Deep Reinforcement Learning in Parameterized Action Space 2016
Matthew Hausknecht and Peter Stone, In Proceedings of the International Conference on Learning Representations (ICLR), San Juan, Puerto Rico, May 2016.
Delta-Tolling: Adaptive Tolling for Optimizing Traffic Throughput 2016
Guni Sharon, Josiah Hanna, Tarun Rambha, Michael Albert, Peter Stone, and Stephen D. Boyles, In Proceedings of the 9th International Workshop on Agents in Traffic and Transportation (ATT 2016), New York, NY, USA, July 2016.
Discovering Multimodal Behavior in Ms. Pac-Man through Evolution of Modular Neural Networks 2016
Jacob Schrum and Risto Miikkulainen, IEEE Transactions on Computational Intelligence and AI in Games, Vol. 8, 1 (2016), pp. 67--81.
Distributed Age-Layered Novelty Search 2016
Babak Hodjat, Hormoz Shahrzad, and Risto Miikkulainen, To Appear In Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (Alife'16, Cancun, Mexico) 2016.
Dynamically Constructed (PO)MDPs for Adaptive Robot Planning 2016
Shiqi Zhang, Piyush Khandelwal, and Peter Stone, In IJCAI'16 Workshop on Autonomous Mobile Service Robots, New York City, USA, July 2016.
Estimating the Advantage of Age-Layering in Evolutionary Algorithms 2016
Hormoz Shahrzad, Babak Hodjat, and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2016, Denver, CO) 2016.
Evolving Artificial Language Through Evolutionary Reinforcement Learning 2016
Xun Li and Risto Miikkulainen, In Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems, Cambridge, MA, 2016. MIT Press.
Evolving Deep LSTM-based Memory networks using an Information Maximization Objective 2016
Aditya Rawal and Risto Miikkulainen, To Appear In Genetic and Evolutionary Computation Conference (GECCO 2016), Colorado, USA 2016.
First-Order Modular Logic Programs and their Conservative Extensions 2016
Amelia Harrison and Yuliya Lierler, Theory and Practice of Logic Programming, Vol. 16, 5-6 (2016), pp. 755--770.
Grounded Semantic Networks for Learning Shared Communication Protocols 2016
Matthew Hausknecht and Peter Stone, In Deep Reinforcement Learning, NIPS Workshop, Barcelona, Spain, December 2016.
Half Field Offense: An Environment for Multiagent Learning and Ad Hoc Teamwork 2016
Matthew Hausknecht, Prannoy Mupparaju, Sandeep Subramanian, Shivaram Kalyanakrishnan, and Peter Stone, In AAMAS Adaptive Learning Agents (ALA) Workshop, Singapore, May 2016.
Improved Semantic Parsers For If-Then Statements 2016
I. Beltagy and Chris Quirk, To Appear In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), Berlin, Germany 2016.
Improving LSTM-based Video Description with Linguistic Knowledge Mined from Text 2016
Subhashini Venugopalan, Lisa Anne Hendricks, Raymond Mooney, and Kate Saenko, In Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing (EMNLP-16), pp. 1961--1966, Austin, Texas 2016.
Intelligent Instantiation and Supersafe Rules 2016
Vladimir Lifschitz, In Technical Communications of the 32nd International Conference on Logic Programming 2016.
Learning Behavior Characterizations for Novelty Search 2016
Elliot Meyerson, Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2016), Denver, Colorado 2016. ACM.
Learning Multi-Modal Grounded Linguistic Semantics by Playing "I Spy" 2016
Jesse Thomason, Jivko Sinapov, Maxwell Svetlik, Peter Stone, and Raymond J. Mooney, In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI-16), pp. 3477--3483, New York City 2016.
Learning Statistical Scripts with LSTM Recurrent Neural Networks 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, February 2016.
Learning to Order Objects Using Haptic and Proprioceptive Exploratory Behaviors 2016
Jivko Sinapov, Priyanka Khante, Maxwell Svetlik, and Peter Stone, In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), New York City, USA, Jult 2016.
Machine Learning Capabilities of a Simulated Cerebellum 2016
Matthew Hausknecht, Wen-Ke Li, Michael Mauk, and Peter Stone, IEEE Transactions on Neural Networks and Learning Systems (2016).
Machines Are Becoming More Creative Than Humans 2016
Risto Miikkulainen, VentureBeat, Vol. 2016/04/03 (2016).
Making Friends on the Fly: Cooperating with New Teammates 2016
Samuel Barrett, Avi Rosenfeld, Sarit Kraus, and Peter Stone, Artificial Intelligence (2016).
MARLEDA: Effective Distribution Estimation through Markov Random Fields 2016
Matthew Alden and Risto Miikkulainen, Theoretical Computer Science, Vol. 633 (2016), pp. 4-18.
MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification 2016
Ye Zhang, Stephen Roller, and Byron Wallace., In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), pp. 1522--1527, San Diego, California 2016.
Minimum Cost Matching for Autonomous Carsharing 2016
Josiah P. Hanna, Michael Albert, Donna Chen, and Peter Stone, In Proceedings of the 9th IFAC Symposium on Intelligent Autonomous Vehicles (IAV 2016), Leipzig, Germany, June 2016.
Multirobot Symbolic Planning under Temporal Uncertainty 2016
Shiqi Zhang, Yuqian Jiang, Guni Sharon, and Peter Stone, In IJCAI'16 Workshop on Autonomous Mobile Service Robots, New York City, USA, July 2016.
Natural Language Semantics Using Probabilistic Logic 2016
I. Beltagy, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star 2016
Babak Hodjat, Hormoz Shahrzad, In Genetic Programming Theory and Practice XIII, 2016. Springer, Cham.
Object-Model Transfer in the General Video Game Domain 2016
Alexander Braylan, Risto Miikkulainen, To Appear In Proceedings of the Twelfth AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 2016.
On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search 2016
Khandelwal, Piyush, Liebman, Elad, Niekum, Scott, Stone, and Peter, In Proceedings of The 33rd International Conference on Machine Learning, pp. 1319--1328, New York City, NY, USA, June 2016.
On-Policy vs. Off-Policy Updates for Deep Reinforcement Learning 2016
Matthew Hausknecht and Peter Stone, In Deep Reinforcement Learning: Frontiers and Challenges, IJCAI Workshop, New York, July 2016.
PIC a Different Word: A Simple Model for Lexical Substitution in Context 2016
Stephen Roller and Katrin Erk, In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-16), pp. 1121-1126, San Diego, California 2016.
Prioritized Role Assignment for Marking 2016
Patrick MacAlpine and Peter Stone, In {R}obo{C}up 2016: Robot Soccer World Cup {XX}, Sven Behnke and Daniel D. Lee and Sanem Sariel and Raymond Sheh (Eds.), Berlin 2016. Springer Verlag.
Proving Infinitary Formulas 2016
Amelia Harrison, Vladimir Lifschitz, and Julian Michael, Theory and Practice of Logic Programming, Vol. 16, 5-6 (2016), pp. 787--799.
Representing Meaning with a Combination of Logical and Distributional Models 2016
I. Beltagy, Stephen Roller, Pengxiang Cheng, Katrin Erk, and Raymond J. Mooney, The special issue of Computational Linguistics on Formal Distributional Semantics, Vol. 42, 4 (2016).
Reuse of Neural Modules for General Video Game Playing 2016
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, To Appear In Proceedings of the 30th AAAI Conference on Artificial Intelligence (AAAI-16) 2016.
Robot Scavenger Hunt: A Standardized Framework for Evaluating Intelligent Mobile Robots 2016
Shiqi Zhang, Dongcai Lu, Xiaoping Chen, and Peter Stone, In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), New York City, USA, July 2016.
Robust Automated Mechanism Design 2016
Michael Albert, Vincent Conitzer, and Peter Stone, In Proceedings of the EC 2016 2nd Algorithmic Game Theory and Data Science Workshop, Netherlands, July 2016.
Solving Multiple Isolated, Interleaved, and Blended Tasks through Modular Neuroevolution 2016
Jacob Schrum and Risto Miikkulainen, Evolutionary Computation, Vol. 24, 3 (2016), pp. 459--490. MIT Press.
Source Task Creation for Curriculum Learning 2016
Sanmit Narvekar, Jivko Sinapov, Matteo Leonetti, and Peter Stone, In Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), Singapore, May 2016.
Special Issue on Multiagent Interaction without Prior Coordination: Guest Editorial 2016
Stefano Albrecht, Somchaya Liemhetcharat, and Peter Stone, Autonomous Agents and Multi-Agent Systems (2016).
Stable Models for Infinitary Formulas with Extensional Atoms 2016
Amelia Harrison and Vladimir Lifschitz, Theory and Practice of Logic Programming, Vol. 15, 5-6 (2016), pp. 771--786.
Stacking With Auxiliary Features 2016
Nazneen Fatema Rajani and Raymond J. Mooney, ArXiv preprint arXiv:1605.08764 (2016).
Stacking With Auxiliary Features for Combining Supervised and Unsupervised Ensembles 2016
Nazneen Fatema Rajani and Raymond J. Mooney, In Proceedings of the Ninth Text Analysis Conference (TAC 2016) 2016.
Stacking With Auxiliary Features: Improved Ensembling for Natural Language and Vision 2016
Nazneen Fatema Rajani, PhD proposal, Department of Computer Science, The University of Texas at Austin.
State Aggregation through Reasoning in Answer Set Programming 2016
Ginevra Gaudioso, Matteo Leonetti, and Peter Stone, In Proceedings of the IJCAI Workshop on Autonomous Mobile Service Robots (WSR 16), New York City, NY, USA, July 2016.
Statistical Script Learning with Recurrent Neural Networks 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the Workshop on Uphill Battles in Language Processing (UBLP) at EMNLP 2016, Austin, TX, November 2016.
Surrogate-based Evolutionary Optimization for Friction Stir Welding 2016
Cem C Tutum, Shaayaan Sayed and Risto Miikkulainen, In Proceedings of IEEE World Congress on Computational Intelligence (WCCI 2016), pp. 8 pages, Vancouver, BC, Canada, July 2016.
The Evolution of Coordinated Cooperative Behaviors 2016
Padmini Rajagopalan, PhD Thesis, Department of Computer Science, University of Texas at Austin.
The Evolution of Language Groups among Cooperating Digital Predators 2016
Patrick Haley, Technical Report HR-16-06, Department of Computer Science, The University of Texas at Austin.
Three Years of the RoboCup Standard Platform League Drop-in Player Competition: Creating and Maintaining a Large Scale Ad Hoc Teamwork Robotics Competition 2016
Katie Genter, Tim Laue, and Peter Stone, Journal of Autonomous Agents and Multi-Agent Systems (JAAMAS) (2016), pp. 1--31. Springer.
Using Sentence-Level LSTM Language Models for Script Inference 2016
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (ACL-16), pp. 279--289, Berlin, Germany 2016.
Bin-Based Estimation of the Amount of Effort for Embedded Software Development Projects with Support Vector Machines 2016
Kazunori Iwata, Elad Liebman, Peter Stone, Toyoshiro Nakashima, Yoshiyuki Anan, and Naohiro Ishii, In {C}omputer and {I}nformation {S}cience , Roger Lee (Eds.), Berlin 2016. Springer Verlag.
Impact of Music on Decision Making in Quantitative Tasks 2016
Elad Liebman, Peter Stone, and Corey N. White, In 17th International Society for Music Information retrieval Conference (ISMIR), NYC, USA, August 2016.
UT Austin Villa RoboCup 3D Simulation Base Code Release 2016
Patrick MacAlpine and Peter Stone, In {R}obo{C}up 2016: Robot Soccer World Cup {XX}, Sven Behnke and Daniel D. Lee and Sanem Sariel and Raymond Sheh (Eds.), Berlin 2016. Springer Verlag.
UT Austin Villa: RoboCup 2015 3D Simulation League Competition and Technical Challenges Champions 2016
Patrick MacAlpine, Josiah Hanna, Jason Liang, and Peter Stone, In {R}obo{C}up-2015: Robot Soccer World Cup {XIX}, Luis Almeida and Jianmin Ji and Gerald Steinbauer and Sean Luke (Eds.), Berlin, Germany 2016. Springer Verlag.
UT Austin Villa: RoboCup 2016 3D Simulation League Competition and Technical Challenges Champions 2016
Patrick MacAlpine and Peter Stone, In {R}obo{C}up 2016: Robot Soccer World Cup {XX}, Sven Behnke and Daniel D. Lee and Sanem Sariel and Raymond Sheh (Eds.) 2016. Springer.
Extinction Events Can Accelerate Evolution 2015
Joel Lehman and Risto Miikkulainen, PLoS ONE, Vol. 10(8) (2015), pp. e0132886 https://doi.org/10.13.
A Direct Proof of Hosoi's Theorem (Extended Abstract) 2015
Amelia Harrison, Vladimir Lifschitz, David Pearce, and Agustin Valverde, In Abstracts of Papers Presented at the Third St. Petersburg Days of Logic and Computability 2015.
A Supertag-Context Model for Weakly-Supervised CCG Parser Learning 2015
Dan Garrette, Chris Dyer, Jason Baldridge, and Noah A. Smith , In Proceedings of the 2015 Conference on Computational Natural Language Learning (CoNLL-2015), pp. 22--31, Beijing, China 2015.
Abstract Gringo 2015
Martin Gebser, Amelia Harrison, Roland Kaminski, Vladimir Lifschitz, and Torsten Schaub, Theory and Practice of Logic Programming, Vol. 15, 4-5 (2015).
Autonomous Intersection Management for Semi-Autonomous Vehicles 2015
Tsz-Chiu Au, Shun Zhang and Peter Stone, In Handbook of Transportation, May 2015.
Autonomous Trading in Modern Electricity Markets 2015
Daniel Urieli, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Code and binaries available at: http://www.cs.utexas.edu/~urieli/thesis.
Benchmarking Robot Cooperation without Pre-Coordination in the RoboCup Standard Platform League Drop-In Player Competition 2015
Katie Genter, Tim Laue, and Peter Stone, In Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-15), Hamburg, Germany, September 2015.
Cooperating with Unknown Teammates in Complex Domains: A Robot Soccer Case Study of Ad Hoc Teamwork 2015
Samuel Barrett and Peter Stone, In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, January 2015.
CORPP: Commonsense Reasoning and Probabilistic Planning, as Applied to Dialog with a Mobile Robot 2015
Shiqi Zhang and Peter Stone, In Proceedings of the 29th Conference on Artificial Intelligence (AAAI), January 2015.
Deep Recurrent Q-Learning for Partially Observable MDPs 2015
Matthew Hausknecht and Peter Stone, In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (AAAI-SDMIA15), Arlington, Virginia, USA, November 2015.
Determining Placements of Influencing Agents in a Flock 2015
Katie Genter, Shun Zhang, and Peter Stone, In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems (AAMAS-15), Istanbul, Turkey, May 2015.
DJ-MC: A Reinforcement-Learning Agent for Music Playlist Recommendation 2015
Elad Liebman, Maytal Saar-Tsechansky, and Peter Stone, In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.
Enhancing Divergent Search through Extinction Events 2015
Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, Spain 2015.
Evaluating team behaviors constructed with human-guided machine learning 2015
Igor V. Karpov, Leif M. Johnson and Risto Miikkulainen, To Appear In Proceedings of the IEEE Conference on Computational Intelligence in Games, August 31-July 2 2015.
Evolutionary Bilevel Optimization for Complex Control Problems and Blackbox Function Optimization 2015
Jason Zhi Liang, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin.
Evolutionary Bilevel Optimization for Complex Control Tasks 2015
Jason Zhi Liang, Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015), pp. 871–878, Madrid, Spain, July 2015.
Evolving Scout Agents for Military Simulations 2015
Brian D. Boyles, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin.
Evolving Strategies for Social Innovation Games 2015
Erkin Bahceci, Riitta Katila and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015), Madrid, Spain 2015.
Frame Skip Is a Powerful Parameter for Learning to Play Atari 2015
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, In AAAI-15 Workshop on Learning for General Competency in Video Games 2015.
Framing reinforcement learning from human reward: Reward positivity, temporal discounting, episodicity, and performance 2015
W. Bradley Knox and Peter Stone, Artificial Intelligence, Vol. 225 (2015).
General Video Game Playing as a Benchmark for Human-Competitive AI 2015
Joel Lehman and Risto Miikkulainen, In AAAI-15 Workshop on Beyond the Turing Test 2015.
How Music Alters Decision Making: Impact of Music Stimuli on Emotional Classification 2015
Elad Liebman, Peter Stone, and Corey N. White, In 16th International Society for Music Information Retrieval Conference (ISMIR), Malaga, Spain, October 2015.
In Memoriam: Grigori E. Mints 2015
Solomon Feferman and Vladimir Lifschitz, Bulletin of Symbolic Logic, Vol. 21 (2015).
Inducing Grammars from Linguistic Universals and Realistic Amounts of Supervision 2015
Dan Garrette, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Infinitary Equilibrium Logic and Strong Equivalence 2015
Amelia Harrison, Vladimir Lifschitz, David Pearce, and Agustin Valverde, In Logic Programming and Nonmonotonic Reasoning, 13th International Conference (LPNMR), Francesco Calimeri, Giovambattista Ianni, Miroslaw Truszczynski (Eds.) 2015.
Infinitary Formulas in Answer Set Programming 2015
Amelia Harrison, Vladimir Lifschitz, and Miroslaw Truszczynski, ALP Newsletter (2015).
Intrinsically motivated model learning for developing curious robots 2015
Todd Hester and Peter Stone, Artificial Intelligence (2015). Elsevier.
Keyframe Sampling, Optimization, and Behavior Integration: Towards Long-Distance Kicking in the RoboCup 3D Simulation League 2015
Mike Depinet, Patrick MacAlpine, and Peter Stone, In {R}obo{C}up-2014: Robot Soccer World Cup {XVIII}, H. Levent Akin and Reinaldo A. C. Bianchi and Subramanian Ramamoorthy and Komei Sugiura (Eds.) 2015. Springer Verlag.
Knowledge Base Population using Stacked Ensembles of Information Extractors 2015
Vidhoon Viswanathan, Masters Thesis, Department of Computer Science, The University of Texas at Austin.
Knowledge Transfer Using Latent Variable Models 2015
Ayan Acharya, PhD Thesis, Department of Electrical and Computer Engineering, The University of Texas at Austin.
Language to Code: Learning Semantic Parsers for If-This-Then-That Recipes 2015
Chris Quirk, Raymond Mooney, and Michel Galley, In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-15), pp. 878--888, Beijing, China, July 2015.
Leading the Way: An Efficient Multi-robot Guidance System 2015
Piyush Khandelwal, Samuel Barrett, and Peter Stone, In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.
Learning Inter-Task Transferability in the Absence of Target Task Samples 2015
Jivko Sinapov, Sanmit Narvekar, Matteo Leonetti, and Peter Stone, In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.
Learning to Interpret Natural Language Commands through Human-Robot Dialog 2015
Jesse Thomason, Shiqi Zhang, Raymond Mooney, and Peter Stone, In Proceedings of the 2015 International Joint Conference on Artificial Intelligence (IJCAI), pp. 1923--1929, Buenos Aires, Argentina, July 2015.
Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training 2015
Manish Saggar, Anthony P. Zanesco, Brandon G. King, David A. Bridwell, Katherine A. MacLean, Stephen R. Aichele, Tonya L. Jacobs, B. Alan Wallace, Clifford D. Saron, Risto Miikkulainen, NeuroImage, Vol. 114 (2015), pp. 88-104. Elsevier.
Mobile Robot Planning using Action Language BC with an Abstraction Hierarchy 2015
Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone, In Proceedings of the 13th International Conference on Logic Programming and Non-monotonic Reasoning (LPNMR), Lexington, KY, USA, September 2015.
Monte Carlo Hierarchical Model Learning 2015
Jacob Menashe and Peter Stone, In Proceedings of the 14th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Istanbul, Turkey, May 2015.
Natural Language Video Description using Deep Recurrent Neural Networks 2015
Subhashini Venugopalan, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Neuroevolution 2015
Risto Miikkulainen, In Encyclopedia of Machine Learning, 2nd Edition, Sammut, C. and Webb, G. I. (Eds.), Berlin, 2015. Springer.
On Equivalence of Infinitary Formulas under the Stable Model Semantics 2015
Amelia Harrison, Vladimir Lifschitz and Miroslaw Truszczynski, Theory and Practice of Logic Programming , Vol. 15, 1 (2015).
On the Cross-Domain Reusability of Neural Modules for General Video Game Playing 2015
Alexander Braylan, Mark Hollenbeck, Elliot Meyerson and Risto Miikkulainen, In IJCAI'15 Workshop on General Intelligence in Game-Playing Agents, pp. 7--14 2015.
On the Proper Treatment of Quantifiers in Probabilistic Logic Semantics 2015
I. Beltagy and Katrin Erk, In Proceedings of the 11th International Conference on Computational Semantics (IWCS-2015), London, UK, April 2015.
Pearl's Causality In a Logical Setting 2015
Alexander Bochman and Vladimir Lifschitz, In Proceedings of the AAAI Conference on Artificial Intelligence 2015.
Representative Selection in Nonmetric Datasets 2015
Elad Liebman, Benny Chor, and Peter Stone, Applied Artificial Intelligence, Vol. 29, 8 (2015), pp. 807--838.
Robot-centric Activity Recognition "in the Wild" 2015
Gori, I., Sinapov, J., Khante, P., Stone, P., and Aggarwal, J.K., In Proceedings of the International Conference on Social Robotics (ICSR), October 2015.
Sensorimotor Embedding: A Developmental Approach to Learning Geometry 2015
Jeremy Stober, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Sequence to Sequence -- Video to Text 2015
Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue, Raymond J. Mooney, Trevor Darrell, and Kate Saenko, In Proceedings of the 2015 International Conference on Computer Vision (ICCV-15), Santiago, Chile, December 2015.
Solving Interleaved and Blended Sequential Decision-Making Problems through Modular Neuroevolution 2015
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2015), pp. 345--352, Madrid, Spain, July 2015. Best Paper: Digital Entertainment and Arts.
Stacked Ensembles of Information Extractors for Knowledge-Base Population 2015
Vidhoon Viswanathan, Nazneen Fatema Rajani, Yinon Bentor, and Raymond J. Mooney, In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics (ACL-15), pp. 177-187, Beijing, China, July 2015.
Stacked Ensembles of Information Extractors for Knowledge-Base Population by Combining Supervised and Unsupervised Approaches 2015
Nazneen Fatema Rajani and Raymond J Mooney, In Proceedings of the Eighth Text Analysis Conference (TAC 2015), November 2015.
Statistical Script Learning with Recurrent Neural Nets 2015
Karl Pichotta, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System 2015
Hormoz Shahrzad, Babak Hodjat, In Genetic Programming Theory and Practice XII, Riolo, R., Worzel, W., Kotanchek, M. (Eds.), University of Michigan, Ann Arbor, USA, May 2015. Springer International Publishing Switzerland.
The Dramatic True Story of the Frame Default 2015
Vladimir Lifschitz, Journal of Philosophical Logic, Vol. 44, 2 (2015), pp. 163--176.
The Impact of Determinism on Learning Atari 2600 Games 2015
Matthew Hausknecht and Peter Stone, In AAAI Workshop on Learning for General Competency in Video Games, Austin, Texas, USA, January 2015.
The Theory of Correlation Formulas and Their Application to Discourse Coherence 2015
Julian Michael, Undergraduate Honors Thesis, Department of Computer Science, University of Texas at Austin.
The Winograd Schema Challenge and Reasoning about Correlation 2015
Daniel Bailey, Amelia Harrison, Yuliya Lierler, Vladimir Lifschitz, and Julian Michael, In Working Notes of the Symposium on Logical Formalizations of Commonsense Reasoning 2015. AAAI Press.
Translating Videos to Natural Language Using Deep Recurrent Neural Networks 2015
Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney, and Kate Saenko, In Proceedings the 2015 Conference of the North American Chapter of the Association for Computational Linguistics -- Human Language Technologies (NAACL HLT 2015), pp. 1494--1504, Denver, Colora...
Unsupervised Code-Switching for Multilingual Historical Document Transcription 2015
Dan Garrette, Hannah Alpert-Abrams, Taylor Berg-Kirkpatrick, and Dan Klein , In Proceedings the 2015 Conference of the North American Chapter of the Association for Computational Linguistics -- Human Language Technologies (NAACL HLT 2015), pp. 1036--1041, Denver, Colora...
Weakly-Supervised Grammar-Informed Bayesian CCG Parser Learning 2015
Dan Garrette, Chris Dyer, Jason Baldridge, Noah A. Smith, In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, TX, January 2015.
SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning 2015
Patrick MacAlpine, Eric Price, and Peter Stone, In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
UT Austin Villa 2014: RoboCup 3D Simulation League Champion via Overlapping Layered Learning 2015
Patrick MacAlpine, Mike Depinet, and Peter Stone, In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January 2015.
UT Austin Villa: RoboCup 2014 3D Simulation League Competition and Technical Challenge Champions 2015
Patrick MacAlpine, Mike Depinet, Jason Liang, and Peter Stone, In {R}obo{C}up-2014: Robot Soccer World Cup {XVIII}, H. Levent Akin and Reinaldo A. C. Bianchi and Subramanian Ramamoorthy and Komei Sugiura (Eds.) 2015. Springer Verlag.
Active Multitask Learning Using Both Latent and Supervised Shared Topics 2014
Ayan Acharya, Raymond J. Mooney, and Joydeep Ghosh, In Proceedings of the 2014 SIAM International Conference on Data Mining (SDM14), Philadelphia, Pennsylvania, April 2014.
Adapting Morphology to Multiple Tasks in Evolved Virtual Creatures 2014
Dan Lessin, Don Fussell, Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) 2014 2014.
An Anarchy of Methods: Current Trends in How AI is Abstracted in AI 2014
Joel Lehman, Jeff Clune and Sebastian Risi, Intelligent Systems magazine, Vol. 29, 6 (2014), pp. 56-62.
Communicating with Unknown Teammates 2014
Samuel Barrett, Noa Agmon, Noam Hazon, Sarit Kraus, and Peter Stone, In Proceedings of the Twenty-First European Conference on Artificial Intelligence, August 2014.
Competitive Multi-Agent Search 2014
Erkin Bahceci, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Cooperating with Unknown Teammates in Robot Soccer 2014
Samuel Barrett and Peter Stone, In AAMAS Autonomous Robots and Multirobot Systems Workshop (ARMS 2014), May 2014.
Cooperating with Unknown Teammates in Robot Soccer 2014
Samuel Barrett and Peter Stone, In AAAI Workshop on Multiagent Interaction without Prior Coordination (MIPC 2014), July 2014.
Efficient Markov Logic Inference for Natural Language Semantics 2014
I. Beltagy and Raymond J. Mooney, In Proceedings of the Fourth International Workshop on Statistical Relational AI at AAAI (StarAI-2014), pp. 9--14, Quebec City, Canada, July 2014.
Evolution of Communication in Mate Selection 2014
Aditya Rawal, Janette Boughman and Risto Miikkulainen, To Appear In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) , New York, USA, July, 2014 2014.
Evolutionary Annealing: Global Optimization in Arbitrary Measure Spaces 2014
Alan J Lockett and Risto Miikkulainen, Journal of Global Optimization, Vol. 58 (2014), pp. 75-108.
Evolved Virtual Creatures as Content: Increasing Behavioral and Morphological Complexity 2014
Dan Lessin, PhD Thesis, Computer Science Department, The University of Texas at Austin. Tech Report TR-15-01.
Evolving Multimodal Behavior Through Modular Multiobjective Neuroevolution 2014
Jacob Schrum, PhD Thesis, The University of Texas at Austin. Tech Report TR-14-07.
Evolving Multimodal Behavior Through Subtask and Switch Neural Networks 2014
Xun Li and Risto Miikkulainen, In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14) 2014.
Evolving Multimodal Behavior With Modular Neural Networks in Ms. Pac-Man 2014
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), pp. 325--332, Vancouver, BC, Canada, July 2014. Best Paper: Digital Entertainment and Arts.
General Intelligence through Prolonged Evolution of Densely Connected Neural Networks 2014
Padmini Rajagopalan, Aditya Rawal, Kay E. Holekamp and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), Vancouver, BC, Canada, July 2014.
GRADE: Machine Learning Support for Graduate Admissions 2014
Austin Waters, Risto Miikkulainen, AI Magazine, Vol. 35 (2014), pp. 64-75.
Grasping Novel Objects with a Dexterous Robotic Hand through Neuroevolution 2014
Pei-Chi Huang, Joel Lehman, Aloysius K. Mok, Risto Miikkulainen, Luis Sentis, In IEEE Symposium Series on Computational Intelligence 2014. IEEE.
Inclusive yet Selective: Supervised Distributional Hypernymy Detection 2014
Stephen Roller, Katrin Erk, and Gemma Boleda, In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), pp. 1025--1036, Dublin, Ireland, August 2014.
Infinite-Word Topic Models for Digital Media 2014
Austin Waters, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Influencing a Flock via Ad Hoc Teamwork 2014
Katie Genter and Peter Stone, In Proceedings of the Ninth International Conference on Swarm Intelligence (ANTS 2014), September 2014.
Integrating Language and Vision to Generate Natural Language Descriptions of Videos in the Wild 2014
Jesse Thomason, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, and Raymond Mooney, In Proceedings of the 25th International Conference on Computational Linguistics (COLING 2014), pp. 1218--1227, Dublin, Ireland, August 2014.
Integrating Visual and Linguistic Information to Describe Properties of Objects 2014
Calvin MacKenzie, Undergraduate Honors Thesis, Computer Science Department, University of Texas at Austin.
Learning Decision Lists with Lags for Physiological Time Series 2014
Erik Hemberg, Kalyan Veeramachaneni, Prashan Wanigasekara, Hormoz Shahrzad, Babak Hodjat, Una-May O'Reilly, In Workshop on Data Mining for Medicine and Healthcare at the 14th SIAM International Conference on Data Mining, pp. 82-87, 2014.
Maintenance of a Long Running Distributed Genetic Programming System for Solving Problems Requiring Big Data 2014
Babak Hodjat, Erik Hemberg, Hormoz Shahrzad, Una-May O’Reilly, In Genetic Programming Theory and Practice XI, Riolo, R., Moore, J., Kotanchek, M. (Eds.), University of Michigan, Ann Arbor, USA, May 2014. Springer, New York, NY..
Mobile Robot Planning using Action Language BC with Hierarchical Domain Abstractions 2014
Shiqi Zhang, Fangkai Yang, Piyush Khandelwal, and Peter Stone, In The 7th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP), July 2014.
Modeling Uncertainty in Leading Ad Hoc Teams 2014
Noa Agmon, Samuel Barrett, and Peter Stone, In Proc. of 13th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2014.
Multi-robot Human Guidance using Topological Graphs 2014
Piyush Khandelwal and Peter Stone, In AAAI Spring 2014 Symposium on Qualitative Representations for Robots (AAAI-SSS), March 2014.
Natural Language Semantics using Probabilistic Logic 2014
I. Beltagy, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Orienting a Flock via Ad Hoc Teamwork 2014
Katie Genter and Peter Stone, In Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014), May 2014.
Overcoming Deception in Evolution of Cognitive Behaviors 2014
Joel Lehman and Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2014), Vancouver, BC, Canada, July 2014.
Plan Recognition Using Statistical Relational Models 2014
Sindhu Raghavan, Parag Singla, and Raymond J. Mooney, In Plan, Activity, and Intent Recognition: Theory and Practice, Sukthankar, G. and Geib, C. and Bui, H.H. and Pynadath, D. and Goldman, R.P. (Eds.), pp. 57--85, Burlington, MA 2014. Morgan Kauf...
Planning in Action Language BC while Learning Action Costs for Mobile Robots 2014
Piyush Khandelwal, Fangkai Yang, Matteo Leonetti, Vladimir Lifschitz, and Peter Stone, In International Conference on Automated Planning and Scheduling (ICAPS), June 2014.
Planning in Answer Set Programming while Learning Action Costs for Mobile Robots 2014
Fangkai Yang, Piyush Khandelwal, Matteo Leonetti, and Peter Stone, No other information
Probabilistic Soft Logic for Semantic Textual Similarity 2014
I. Beltagy, Katrin Erk, and Raymond J. Mooney, In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL-14), pp. 1210--1219, Baltimore, MD 2014.
Representing Actions in Logic-Based Languages 2014
Fangkai Yang, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Semantic Parsing using Distributional Semantics and Probabilistic Logic 2014
I. Beltagy, Katrin Erk, and Raymond Mooney, In Proceedings of ACL 2014 Workshop on Semantic Parsing (SP-2014), pp. 7--11, Baltimore, MD, June 2014.
Statistical Script Learning with Multi-Argument Events 2014
Karl Pichotta and Raymond J. Mooney, In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2014), pp. 220--229, Gothenburg, Sweden, April 2014.
TacTex'13: A Champion Adaptive Power Trading Agent 2014
Daniel Urieli and Peter Stone, In Proceedings of the Twenty-Eighth Conference on Artificial Intelligence (AAAI 2014), July 2014.
The Evolution of General Intelligence 2014
Padmini Rajagopalan, Kay E. Holekamp and Risto Miikkulainen, In Proceedings of The Fourteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFE 14), New York, NY 2014.
The Semantics of Gringo and Infinitary Propositional Formulas 2014
Amelia Harrison, Vladimir Lifschitz and Fangkai Yang, In Proceedings of 14th International Conference on Principles of Knowledge Representation and Reasoning (KR) 2014.
The RoboCup 2013 Drop-In Player Challenges: A Testbed for Ad Hoc Teamwork 2014
Patrick MacAlpine, Katie Genter, Samuel Barrett, and Peter Stone, In Proc. of 13th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2014. Accompanying videos at
Trading Control Intelligence for Physical Intelligence: Muscle Drives in Evolved Virtual Creatures 2014
Dan Lessin, Don Fussell, Risto Miikkulainen, To Appear In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) 2014 2014.
University of Texas at Austin KBP 2014 Slot Filling System: Bayesian Logic Programs for Textual Inference 2014
Yinon Bentor, Vidhoon Viswanathan, and Raymond Mooney , In Proceedings of the Seventh Text Analysis Conference: Knowledge Base Population (TAC 2014) 2014.
UTexas: Natural Language Semantics using Distributional Semantics and Probabilistic Logic 2014
I. Beltagy, Stephen Roller, Gemma Boleda, and Katrin Erk, and Raymond J. Mooney, In The 8th Workshop on Semantic Evaluation (SemEval-2014), pp. 796--801, Dublin, Ireland, August 2014.
Weakly-Supervised Bayesian Learning of a CCG Supertagger 2014
Dan Garrette, Chris Dyer, Jason Baldridge, and Noah A. Smith, In Proceedings of the Eighteenth Conference on Computational Natural Language Learning (CoNLL-2014), pp. 141--150, Baltimore, MD, June 2014.
SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning 2014
Patrick MacAlpine, Eric Price, and Peter Stone, In Proc. of 13th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS), May 2014. Accompanying videos at 2012
Sindhu Raghavan, Raymond J. Mooney, and Hyeonseo Ku, Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (ACL-2012) (2012), pp. 349--358.
Logic Programs with Intensional Functions 2012
Vladimir Lifschitz, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR) 2012.
Moving Object Segmentation Using Motor Signals 2012
Changhai Xu, Jingen Liu, and Benjamin Kuipers, In European Conference on Computer Vision (ECCV 2012) 2012.
Multiagent Learning through Neuroevolution 2012
Risto Miikkulainen, Eliana Feasley, Leif Johnson, Igor Karpov, Padmini Rajagopalan, Aditya Rawal, and Wesley Tansey, In Advances in Computational Intelligence, J. Liu et al. (Eds.), Vol. LNCS 7311, pp. 24-46, Berlin, Heidelberg: 2012. Springer.
On Coordination in Practical Multi-Robot Patrol 2012
Noa Agmon, Chien-Liang Fok, Yehuda Emaliah, Peter Stone, Christine Julien, and Sriram Vishwanath, In {IEEE} International Conference on Robotics and Automation (ICRA), May 2012.
On the Relation of Constraint Answer Set Programming Languages and Algorithms 2012
Yuliya Lierler, AAAI (2012).
PAC Subset Selection in Stochastioc Multi-armed Bandits 2012
Shivaram Kalyanakrishnan, Ambuj Tewari, Peter Auer, and Peter Stone, In In proceedings of the 29th International Conference on Machine Learning (ICML 2012), June-July 2012.
Parsing Combinatory Categorial Grammar via Planning in Answer Set Programming 2012
Yuliya Lierler and Peter Schueller, Correct Reasoning: Essays on Logic-based AI (2012). Springer.
Perturbation based Large Margin Approach for Ranking 2012
Eunho Yang, Ambuj Tewari and Pradeep Ravikumar, In International Conference on Artificial Intelligence and Statistics (AISTATS) 2012.
Practical and Methodological Aspects of the Use of Cutting-Edge ASP Tools 2012
Marcello Balduccini and Yuliya Lierler, Fourteenth International Symposium on Practical Aspects of Declarative Languages (2012), pp. 78-92.
Reinforcement Learning from Human Reward: Discounting in Episodic Tasks 2012
W. Bradley Knox and Peter Stone, In In Proceedings of the 21st IEEE International Symposium on Robot and Human Interactive Communication (Ro-Man), September 2012.
Reinforcement Learning with Human and MDP Reward 2012
W. Bradley Knox and Peter Stone, In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012), June 2012.
Representing First-Order Causal Theories by Logic Programs 2012
Paolo Ferraris, Joohyung Lee, Yuliya Lierler, Vladimir Lifschitz and Fangkai Yang, Theory and Practice of Logic Programming, Vol. 12, 3 (2012), pp. 383-412.
Review Quality Aware Collaborative Filtering 2012
Sindhu Raghavan, Suriya Ganasekar, and Joydeep Ghosh, In Sixth ACM Conference on Recommender Systems (RecSys 2012), pp. 123--130, September 2012.
Role Selection in Ad Hoc Teamwork 2012
Katie Genter, Noa Agmon, and Peter Stone, In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012), June 2012.
Setpoint Scheduling for Autonomous Vehicle Controllers 2012
Tsz-Chiu Au, Michael Quinlan, and Peter Stone, In {IEEE} International Conference on Robotics and Automation (ICRA), May 2012.
Surviving Solver Sensitivity: An ASP Practitioner's Guide 2012
Bryan Silverthorn, Yuliya Lierler and Marius Schneider, International Conference on Logic Programming (ICLP) (2012).
Task decomposition with neuroevolution in extended predator-prey domain 2012
Ashish Jain, Anand Subramoney, Risto Miikkulainen, In Proceedings of Thirteenth International Conference on the Synthesis and Simulation of Living Systems, East Lansing, MI, USA 2012.
TEXPLORE: Temporal Difference Reinforcement Learning for Robots and Time-Constrained Domains. 2012
Todd Hester, PhD Thesis, The University of Texas at Austin. Code available at: http://www.ros.org/wiki/rl-texplore-ros-pkg.
The Common Core of Action Languages B and C 2012
Michael Gelfond and Vladimir Lifschitz, In Working Notes of the International Workshop on Nonmonotonic Reasoning (NMR) 2012.
The Frame Problem, Then and Now 2012
Vladimir Lifschitz, unpublished.
The Nature of Belief-Directed Exploratory Choice in Human Decision-Making 2012
W. Bradley Knox , A. Ross Otto , Peter Stone , and Bradley Love, Frontiers in Psychology, Vol. 2 (2012). The paper can be accessed at: http://www.frontiersin.org/Journal/Abstract.aspx?s=196&name=cognitive_science&ART_DOI=10.3389/fpsyg.2011.00398.
The role of uncertainty and reward on eye movements in a virtual driving task 2012
Brian Sullivan, Leif Johnson, Constantin Rothkopf, Mary Hayhoe and Dana Ballard, Journal of Vision, Vol. 12, 9 (2012).
Two-valued logic programs 2012
Vladimir Lifschitz, In Technical Communications of the International Conference on Logic Programming 2012.
Type-Supervised Hidden Markov Models for Part-of-Speech Tagging with Incomplete Tag Dictionaries 2012
Dan Garrette and Jason Baldridge, In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2012), pp. 821--831, Jeju, Korea, July 2012.
Unsupervised PCFG Induction for Grounded Language Learning with Highly Ambiguous Supervision 2012
Joohyun Kim and Raymond J. Mooney, In Proceedings of the Conference on Empirical Methods in Natural Language Processing and Natural Language Learning (EMNLP-CoNLL '12), pp. 433--444, Jeju Island, Korea, July 2012.
Using a million cell simulation of the cerebellum: Network scaling and task generality 2012
Wen-Ke Li, Matthew J. Hausknecht, Peter Stone, and Michael D. Mauk, Neural Networks (2012).
Using Dynamic Rewards to Learn a Fully Holonomic Bipedal Walk 2012
Patrick MacAlpine and Peter Stone, In AAMAS Adaptive Learning Agents (ALA) Workshop, June 2012.
Video: RoboCup Robot Soccer History 1997 - 2011 2012
Manuela Veloso and Peter Stone, In Proceedings of IROS 2012-IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2012) 2012. Available from http://www.robocup.org/2012/10/robocup-video-finalist-for-best-v...
Weighted-Sequence Problem: ASP vs CASP and Declarative vs Problem Oriented Solving 2012
Yuliya Lierler, Shaden Smith, Miroslaw Truszczynski, Alex Westlund, In Fourteenth International Symposium on Practical Aspects of Declarative Languages 2012.
Austin Villa 2011: Sharing is Caring: Better Awareness through Information Sharing 2012
Samuel Barrett, Katie Genter, Todd Hester, Piyush Khandelwal, Michael Quinlan, Peter Stone, and Mohan Sridharan, Technical Report, Department of Computer Science, The University of Texas at Austin. Tech Report UT-AI-TR-12-01.
RTMBA: A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control 2012
Todd Hester, Michael Quinlan, and Peter Stone, In {IEEE} International Conference on Robotics and Automation (ICRA), May 2012.
TEXPLORE: Real-Time Sample-Efficient Reinforcement Learning for Robots 2012
Todd Hester and Peter Stone, Machine Learning (2012).
UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition 2012
Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, and Peter Stone, In Proc. of 11th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS'12), June 2012.
Wright Eagle and UT Austin Villa: RoboCup 2011 Simulation League Champions 2012
Aijun Bai, Xiaoping Chen, Patrick MacAlpine, Daniel Urieli, Samuel Barrett, and Peter Stone, In {R}obo{C}up-2011: Robot Soccer World Cup {XV} 2012.
Generation of Geometric Programs Specified by Diagrams 2011
Yulin Li, Gordon Novak, Proc. Generative Programming and Component Engineering 2011 (GPCE-11) (2011), pp. 63-72.
A Low Cost Ground Truth Detection System Using the Kinect 2011
Piyush Khandelwal and Peter Stone, In Proceedings of the RoboCup International Symposium 2011 (RoboCup 2011), July 2011.
A modular reinforcement learning model for human visuomotor behavior in a driving task 2011
Brian Sullivan, Leif Johnson, Dana Ballard and Mary Hayhoe, Proceedings of the AISB 2011 Symposium on Architectures for Active Vision. (2011), pp. 33-40.
A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations 2011
David Pardoe and Peter Stone, In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2011), May 2011.
A Real-Time Model-Based Reinforcement Learning Architecture for Robot Control 2011
Todd Hester, Michael Quinlan, and Peter Stone, No other information
A Transition System for AC Language Algorithms 2011
Yuliya Lierler and Yuanlin Zhang, In Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP), 2011 2011.
Abductive Markov Logic for Plan Recognition 2011
Parag Singla and Raymond J. Mooney, Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI-2011) (2011), pp. 1069-1075.
Abductive Plan Recognition by Extending Bayesian Logic Programs 2011
Sindhu Raghavan, Raymond J. Mooney, In Proceedings of the European Conference on Machine Learning/Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2011), Vol. 2, pp. 629-644, September 2011.
Abstract Answer Set Solvers with Backjumping and Learning 2011
Yuliya Lierler, Theory and Practice of Logic Programming (2011).
Ad Hoc Teamwork Modeled with Multi-armed Bandits: An Extension to Discounted Infinite Rewards 2011
Samuel Barrett and Peter Stone, In Tenth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2011.
Adaptive Trading Agent Strategies Using Market Experience 2011
David Merrill Pardoe, No other information
An Integrated Neuroevolutionary Approach to Reactive Control and High-level Strategy 2011
Nate Kohl, Risto Miikkulainen, IEEE Transactions on Evolutionary Computation (2011).
An Introduction to Inter-task Transfer for Reinforcement Learning 2011
Matthew E. Taylor and Peter Stone, AI Magazine, Vol. 32, 1 (2011), pp. 15--34.
ASP-Based Problem Solving with Cutting-Edge Tools 2011
Marcello Balduccini and Yuliya Lierler, In Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP) 2011.
Assisting Machine Learning Through Shaping, Advice and Examples 2011
Igor Karpov, Vinod Valsalam and Risto Miikkulainen, In 2011 IJCAI Workshop on Agents Learning Interactively from Human Teachers (ALIHT), July 2011.
Austin Villa 2010 Standard Platform Team Report 2011
Samuel Barrett, Katie Genter, Matthew Hausknecht, Todd Hester, Piyush Khandelwal, Juhyun Lee, Michael Quinlan, Aibo Tian, Peter Stone, and Mohan Sridharan, Technical Report, Department of Computer Science, The University of Texas at Austin. Tech Report UT-AI-TR-11-01.
Autonomous Intersection Management: Multi-Intersection Optimization 2011
Matthew Hausknecht, Tsz-Chiu Au, and Peter Stone, In Proceedings of IROS 2011-IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), September 2011.
Avoiding Premature Convergence in NeuroEvolution by Broadening the Evolutionary Search 2011
Matthew de Wet, Technical Report HR-11-02, Department of Computer Science, The University of Texas at Austin.
Building a Persistent Workforce on Mechanical Turk for Multilingual Data Collection 2011
David L. Chen and William B. Dolan, In Proceedings of The 3rd Human Computation Workshop (HCOMP 2011), August 2011.
Characterizing Reinforcement Learning Methods through Parameterized Learning Problems 2011
Shivaram Kalyanakrishnan and Peter Stone, Machine Learning (2011).
Collecting Highly Parallel Data for Paraphrase Evaluation 2011
David L. Chen and William B. Dolan, In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics, pp. 190-200, Portland, Oregon, USA, June 2011.
Comparing Agents: Success against People in Security Domains 2011
Raz Lin, Sarit Kraus, Noa Agmon, Samuel Barrett, and Peter Stone, In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, August 2011.
Computational Analysis of Meditation 2011
Manish Saggar, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Constraint Propagation for Efficient Inference in Markov Logic 2011
Tivadar Papai, Parag Singla and Henry Kautz, In Proceedings of 17th International Conference on Principles and Practice of Constraint Programming (CP 2011), 6876, pp. 691-705, September 2011.
Creating Intelligent Agents through Shaping of Coevolution 2011
Adam Dziuk and Risto Miikkulainen, In Proceedings of the Congress on Evolutionary Computation, New Orleans, LA 2011. IEEE.
Creating Intelligent Agents through Shaping of Coevolution 2011
Adam Dziuk, Technical Report HR-11-01, Department of Computer Science, The University of Texas at Austin.
Cross-Cutting Models of Lexical Semantics 2011
Joseph Reisinger and Raymond Mooney, In Proceedings of The Conference on Empirical Methods in Natural Language Processing (EMNLP 2011), pp. 1405-1415, July 2011.
Datalog Programs and Their Stable Models 2011
Vladimir Lifschitz, In Datalog Reloaded: First International Workshop, Datalog 2010, Oxford, UK, March 16-19, 2010. Revised Selected Papers, de Moor, O.; Gottlob, G.; Furche, T.; Sellers, A. (Eds.) 2011. Springer...
Dynamic Lane Reversal in Traffic Management 2011
Matthew Hausknecht, Tsz-Chiu Au, Peter Stone, David Fajardo, and Travis Waller, In Proceedings of IEEE Intelligent Transportation Systems Conference (ITSC), October 2011.
Empirical Evaluation of Ad Hoc Teamwork in the Pursuit Domain 2011
Samuel Barrett, Peter Stone, and Sarit Kraus, Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2011) (2011).
Empowerment for Continuous Agent-Environment Systems 2011
Tobias Jung, Daniel Polani, and Peter Stone, Adaptive Behavior, Vol. 19, 1 (2011), pp. 16-39.
Encoding and Decoding V1 fMRI Responses to Natural Images with Sparse Nonparametric Models 2011
V. Vu, P. Ravikumar, T. Naselaris, K. Kay, J. Gallant, and B. Yu, Annals of Applied Statistics (2011), pp. 1159-1182.
Enforcing Liveness in Autonomous Traffic Management 2011
Tsz-Chiu Au, Neda Shahidi, and Peter Stone, In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence, August 2011.
Evolving Multimodal Networks for Multitask Games 2011
Jacob Schrum and Risto Miikkulainen, In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG 2011), pp. 102--109, Seoul, South Korea, September 2011. IEEE. (Best Paper Award).
Evolving Symmetry for Modular System Design 2011
Vinod K. Valsalam and Risto Miikkulainen, IEEE Transactions on Evolutionary Computation, Vol. 15, 3 (2011), pp. 368--386.
Extending Bayesian Logic Programs for Plan Recognition and Machine Reading 2011
Sindhu V. Raghavan, Technical Report, PhD proposal, Department of Computer Science, The University of Texas at Austin.
Fine-Grained Class Label Markup of Search Queries 2011
Joseph Reisinger and Marius Pasca, In Proceedings of The 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-HLT 2011), pp. 1200-1209, June 2011.
Flood Disaster Mitigation: A Real-world Challenge Problem for Multi-Agent Unmanned Surface Vehicles 2011
Paul Scerri, Balajee Kannan, Pras Velagapudi, Kate Macarthur, Peter Stone, Matthew E. Taylor, John Dolan, Alessandro Farinelli, Archie Chapman, Bernadine Dias, and George Kantor, In Proceedings of the Autonomous Robots and Multirobot Systems workshop (at AAMAS-11), May 2011.
Generation of geometric programs specified by diagrams 2011
Yulin Li and Gordon S. Novak, Jr., In Proceedings of the 10th ACM international conference on Generative programming and component engineering, pp. 63-72, New York, NY, USA 2011. ACM.
Greedy Algorithms for Structurally Constrained High Dimensional Problems 2011
A. Tewari, P. Ravikumar, and I. Dhillon, In Neural Information Processing Systems 2011.
High-dimensional covariance estimation by minimizing l1-penalized log-determinant divergence 2011
P. Ravikumar, M. J. Wainwright, G. Raskutti, and B. Yu, Electronic Journal of Statistics, Vol. 5 (2011), pp. 935-980.
Human-Assisted Neuroevolution Through Shaping, Advice and Examples 2011
Igor V. Karpov, Vinod K. Valsalam and Risto Miikkulainen, In Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, Ireland, July 2011.
Impairment and Rehabilitation in Bilingual Aphasia: A SOM-Based Model 2011
Uli Grasemann, Swathi Kiran, Chaleece Sandberg and Risto Miikkulainen, In Proceedings of WSOM11, 8th Workshop on Self-Organizing Maps, LNCS 6731, J Laaksonen and T. Honkela (Eds.), pp. 207--217, Espoo, Finland 2011. Springer Verlag.
Implementing Weighted Abduction in Markov Logic 2011
James Blythe, Jerry R. Hobbs, Pedro Domingos, Rohit J. Kate, Raymond J. Mooney, In Proceedings of the International Conference on Computational Semantics, pp. 55--64, Oxford, England, January 2011.
Improving the Accuracy and Scalability of Discriminative Learning Methods for Markov Logic Networks 2011
Tuyen N. Huynh, PhD Thesis, Department of Computer Science, University of Texas at Austin.
159 pages.
Integrating Logical Representations with Probabilistic Information using Markov Logic 2011
Dan Garrette, Katrin Erk, Raymond Mooney, In Proceedings of the International Conference on Computational Semantics, pp. 105--114, Oxford, England, January 2011.
John McCarthy, 1927-2011: The Scientist Who Set Computers on the Path to Common Sense 2011
Vladimir Lifschitz, Nature (2011), pp. 480.
Learning and Using Models 2011
Todd Hester and Peter Stone, In Reinforcement Learning: State of the Art 2011.
Learning Geometry from Sensorimotor Experience 2011
Jeremy Stober, Risto Miikkulainen, and Benjamin Kuipers, In Proceedings of the First International Conference on Development and Learning and Epigenetic Robotics, Frankfurt am Main, Germany, August 2011.
Learning Polarity from Structure in SAT 2011
Bryan Silverthorn and Risto Miikkulainen, In Theory and Applications of Satisfiability Testing (SAT) 2011. (extended abstract).
Learning to Interpret Natural Language Navigation Instructions from Observations 2011
David L. Chen and Raymond J. Mooney, Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI-2011) (2011), pp. 859-865.
Measure-Theoretic Evolutionary Annealing 2011
Alan J. Lockett and Risto Miikkulainen, In Proceedings of the 2011 IEEE Congress on Evolutionary Computation 2011.
Modeling Acute and Compensated Language Disturbance in Schizophrenia 2011
Uli Grasemann, Ralph Hoffman and Risto Miikkulainen, In Proceedings of the 33rd Annual Meeting of the Cognitive Science Society 2011.
Motion Segmentation by Learning Homography Matrices from Motor Signals 2011
Changhai Xu and Benjamin Kuipers, Canadian Conference on Computer and Robot Vision (CRV-11) (2011).
Multiagent Patrol Generalized to Complex Environmental Conditions 2011
Noa Agmon, Daniel Urieli, and Peter Stone, In Proceedings of the Twenty-Fifth Conference on Artificial Intelligence (AAAI'11), August 2011.
Nearest Neighbor based Greedy Coordinate Descent 2011
I. Dhillon, P. Ravikumar, and A. Tewari, In Neural Information Processing Systems 2011.
Object Detection Using Principal Contour Fragments 2011
Changhai Xu and Benjamin Kuipers, In Canadian Conference on Computer and Robot Vision (CRV-11) 2011.
On Elementary Loops of Logic Programs 2011
Martin Gebser, Joohyung Lee, Yuliya Lierler, Theory and Practice of Logic Programming (2011).
On Learning Discrete Graphical Models using Greedy Methods 2011
Ali Jalali, Christopher Johnson, and Pradeep Ravikumar, In Neural Information Processing Systems 2011.
On Learning Discrete Graphical Models using Group-Sparse Regularization 2011
A. Jalali, P. Ravikumar, V. Vasuki, and S. Sanghavi, In International Conference on AI and Statistics (AISTATS) 2011.
On Learning with Imperfect Representations 2011
Shivaram Kalyanakrishnan and Peter Stone, In Proceedings of the 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, April 2011.
On NDCG Consistency of Listwise Ranking Methods 2011
Pradeep Ravikumar, Ambuj Tewari and Eunho Yang, International Conference on AI and Statistics (AISTATS) (2011).
On Optimizing Interdependent Skills: A Case Study in Simulated 3D Humanoid Robot Soccer 2011
Daniel Urieli, Patrick MacAlpine, Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone, In Proc. of 10th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS'11), May 2011.
On the Minimality of Stable Models 2011
Paolo Ferraris and Vladimir Lifschitz, In Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning: Essays Dedicated to Michael Gelfond on the Occasion of His 65th Birthday, pp. 54-73 2011. Springer.
On the Use of Variational Inference for Learning Discrete Graphical Models 2011
Eunho Yang and Pradeep Ravikumar, In International Conference on Machine learning (ICML) 2011.
Online Max-Margin Weight Learning for Markov Logic Networks 2011
Tuyen N. Huynh and Raymond J. Mooney, In Proceedings of the Eleventh SIAM International Conference on Data Mining (SDM11), pp. 642--651, Mesa, Arizona, USA, April 2011.
Online Structure Learning for Markov Logic Networks 2011
Tuyen N. Huynh and Raymond J. Mooney, In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2011), Vol. 2, pp. 81-96, September 2011.
Panning for Gold: Finding Relevant Semantic Content for Grounded Language Learning 2011
David L. Chen and Raymond J. Mooney, In Proceedings of Symposium on Machine Learning in Speech and Language Processing (MLSLP 2011), June 2011.
Protecting Against Evaluation Overfitting in Empirical Reinforcement Learning 2011
Shimon Whiteson, Brian Tanner, Matthew E. Taylor, and Peter Stone, In {IEEE} Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL), April 2011.
Real-Space Evolutionary Annealing 2011
Alan J Lockett and Risto Miikkulainen, In Proceedings of the 2011 Genetic and Evolutionary Computation Conference (GECCO-2011) 2011.
Role-Based Ad Hoc Teamwork 2011
Katie Genter, Noa Agmon, and Peter Stone, In Proceedings of the Plan, Activity, and Intent Recognition Workshop at the Twenty-Fifth Conference on Artificial Intelligence (PAIR-11) , August 2011.
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation 2011
C.-J. Hsieh, M. Sustik, I. Dhillon, and P. Ravikumar, In Neural Information Processing Systems 2011.
Stable Models and Circumscription 2011
Paolo Ferraris, Joohyung Lee, and Vladimir Lifschitz, Artificial Intelligence, Vol. 175 (2011), pp. 236--263.
Structure Learning in Ergodic Factored MDPs without Knowledge of the Transition Function's In-Degree 2011
Doran Chakraborty and Peter Stone, In Proceedings of the Twenty Eighth International Conference on Machine Learning (ICML'11), June 2011.
Termination of Grounding is Not Preserved by Strongly Equivalent Transformations 2011
Yuliya Lierler and Vladimir Lifschitz, In Logic Programming and Nonmonotonic Reasoning (LPNMR) 2011.
The Role of Reward Structure, Coordination Mechanism and Net Return in the Evolution of Cooperation 2011
Padmini Rajagopalan, Aditya Rawal, Risto Miikkulainen, Marc A. Wiseman and Kay E. Holekamp, In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG 2011), Seoul, South Korea 2011.
Transition Systems for Model Generators --- A Unifying Approach 2011
Yuliya Lierler and Miroslaw Truszczynski, In International Conference on Logic Programming (ICLP) 2011.
Understanding Human Teaching Modalities in Reinforcement Learning Environments: A Preliminary Report 2011
W. Bradley Knox and Peter Stone, In IJCAI 2011 Workshop on Agents Learning Interactively from Human Teachers (ALIHT), July 2011.
Using Computational Patients to Evaluate Illness Mechanisms in Schizophrenia 2011
Ralph E. Hoffman, Uli Grasemann, Ralitza Gueorguieva, Donald Quinlan, Douglas Lane, and Risto Miikkulainen, Biological Psychiatry, Vol. 69 (2011), pp. 997--1005.
Using visuo-spatial memory for novelty detection 2011
Dmitry Kit, Brian Sullivan and Dana Ballard, Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (2011).
Utilizing Symmetry and Evolutionary Search to Minimize Sorting Networks 2011
Vinod K. Valsalam and Risto Miikkulainen, Technical Report AITR-11-09, Department of Computer Sciences, The University of Texas at Austin.
UT^2: Human-like Behavior via Neuroevolution of Combat Behavior and Replay of Human Traces 2011
Jacob Schrum, Igor V. Karpov and Risto Miikkulainen, In Proceedings of the IEEE Conference on Computational Intelligence and Games (CIG 2011), pp. 329--336, Seoul, South Korea, September 2011. IEEE.
Yet Another Characterization of Strong Equivalence 2011
Alexander Bochman and Vladimir Lifschitz, In Technical Communications of the 27th International Conference on Logic Programming, pp. 11-15 2011.
UT Austin Villa 2011 3D Simulation Team Report 2011
Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, and Peter Stone, Technical Report, Department of Computer Science, The University of Texas at Austin.
A Computational Model of Language Pathology in Schizophrenia 2010
Uli Grasemann, PhD Thesis, Department of Computer Science, The University of Texas at Austin. 147 pages. Technical report TR-11-11.
A Dirty Model for Multi-task Learning 2010
A. Jalali, P. Ravikumar, S. Sanghavi, and C. Ruan, In Neural Information Processing Systems 2010.
A Mixture Model with Sharing for Lexical Semantics 2010
Joseph Reisinger and Raymond J. Mooney, In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2010), pp. 1173--1182, MIT, Massachusetts, USA, October 9--11 2010.
A Particle Filter for Bid Estimation in Ad Auctions with Periodic Ranking Observations 2010
David Pardoe and Peter Stone, In EC 2010 Workshop on Trading Agent Design and Analysis (TADA), Cambridge, Massachusetts 2010.
Accounting for the Relative Importance of Objects in Image Retrieval 2010
S. J. Hwang and K. Grauman, In British Machine Vision Conference (BMVC) 2010.
Adaptive Auction Mechanism Design and the Incorporation of Prior Knowledge 2010
David Pardoe, Peter Stone, Maytal Saar-Tsechansky, Tayfun Keskin, and Kerem Tomak, Informs Journal on Computing, Vol. 22, 3 (2010), pp. 353-370.
An Analysis of Automated Decision Making Methodologies in Role Playing Video Games: Centralized Approach 2010
Christopher Bush, Technical Report HR-10-03, Department of Computer Science, The University of Texas at Austin.
An Analysis of Distributed Decision Making Methodologies in Role Playing Video Games 2010
Matthew Johnston, Technical Report HR-10-09, Department of Computer Science, The University of Texas at Austin.
Asymmetric Region-to-Image Matching for Comparing Images with Generic Object Categories 2010
A. Kovashka and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010.
Authorship Attribution Using Probabilistic Context-Free Grammars 2010
Sindhu Raghavan, Adriana Kovashka and Raymond Mooney, In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (ACL-2010), pp. 38--42 2010.
Autonomous Qualitative Learning of Distinctions and Actions in a Developing Agent 2010
Jonathan Mugan, PhD Thesis, University of Texas at Austin.
Bayesian Abductive Logic Programs 2010
Sindhu Raghavan and Raymond Mooney, In Proceedings of the AAAI-10 Workshop on Statistical Relational AI (Star-AI 10), pp. 82--87, Atlanta, GA, July 2010.
Behavioral, neuroimaging, and computational evidence for perceptual caching in repetition priming 2010
Manish Saggar, Risto Miikkulainen, David Schnyer, Journal of Brain Research, Vol. 1315 (2010), pp. 75--91.
Boosting for Regression Transfer 2010
David Pardoe and Peter Stone, In Proceedings of the 27th International Conference on Machine Learning (ICML 2010), June 2010.
Bringing Simulation to Life: A Mixed Reality Autonomous Intersection 2010
Michael Quinlan, Tsz-Chiu Au, Jesse Zhu, Nicolae Stiurca, and Peter Stone, In Proceedings of IROS 2010-IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), October 2010.
Coevolution of Role-Based Cooperation in Multi-Agent Systems 2010
Chern Han Yong and Risto Miikkulainen, IEEE Transactions on Autonomous Mental Development, Vol. 1 (2010), pp. 170--186.
Collect-Cut: Segmentation with Top-Down Cues Discovered in Multi-Object Images 2010
Y.J. Lee and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010.
Combining Manual Feedback with Subsequent MDP Reward Signals for Reinforcement Learning 2010
W. Bradley Knox and Peter Stone, In Proc. of 9th Int. Conf. on Autonomous Agents and Multiagent Systems (AAMAS 2010), May 2010.
Computational models inform clinical science and assessment: An application to category learning in striatal-damaged patients 2010
W. Todd Maddox, J. Vincent Filoteo and Dagmar Zeithamova, Journal of Mathematical Psychology, Vol. 54, 1 (2010), pp. 109-122.
Constructing Competitive and Cooperative Agent Behavior Using Coevolution 2010
Aditya Rawal, Padmini Rajagopalan and Risto Miikkulainen, In IEEE Conference on Computational Intelligence and Games (CIG 2010), Copenhagen, Denmark, August 2010.
Controlled Kicking under Uncertainty 2010
Samuel Barrett, Katie Genter, Todd Hester, Michael Quinlan, and Peter Stone, In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, Nashville, TN 2010.
Convergence, Targeted Optimality and Safety in Multiagent Learning 2010
Doran Chakraborty and Peter Stone, In Proceedings of the Twenty-seventh International Conference on Machine Learning (ICML 2010), June 2010.
Cross-cutting Models of Distributional Lexical Semantics 2010
Joseph S. Reisinger, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Declarative Query Tuning and Optimization using Answer Set Programming 2010
Yuliya Lierler, Philip Cannata , unpublished. Unpublished draft.
Efficient Selection of Multiple Bandit Arms: Theory and Practice 2010
Shivaram Kalyanakrishnan and Peter Stone, In Proceedings of the 27th International Conference on Machine Learning (ICML 2010) 2010.
Evolving Agent Behavior In Multiobjective Domains Using Fitness-Based Shaping 2010
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010), pp. 439--446, Portland, Oregon, July 2010.
Far-Sighted Active Learning on a Budget for Image and Video Recognition 2010
S. Vijayanarasimhan, P. Jain and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010.
From C-Believed Propositions to the Causal Calculator 2010
Vladimir Lifschitz, Heuristic, Probability and Causality: A Tribute to Judea Pearl (2010).
Gaussian processes for sample efficient reinforcement learning with RMAX-like exploration 2010
Tobias Jung and Peter Stone, In Proceedings of the European Conference on Machine Learning, September 2010.
Generalized Model Learning for Reinforcement Learning on a Humanoid Robot 2010
Todd Hester, Michael Quinlan, and Peter Stone, In International Conference on Robotics and Automation 2010.
Generative Alignment and Semantic Parsing for Learning from Ambiguous Supervision 2010
Joohyun Kim and Raymond J. Mooney, In Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), pp. 543--551, Beijing, China, August 2010.
Hierarchical Neural Networks for Behavior-Based Decision Making 2010
David Robson, Technical Report HR-10-02, Department of Computer Science, The University of Texas at Austin.
Information-theoretic lower bounds on the oracle complexity of sparse convex optimization 2010
A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright, In International Workshop on Optimization for Machine Learning (OPT) 2010.
Joint Entity and Relation Extraction using Card-Pyramid Parsing 2010
Rohit J. Kate and Raymond J. Mooney, In Proceedings of the Fourteenth Conference on Computational Natural Language Learning (CoNLL-2010), pp. 203--212, Uppsala, Sweden, July 2010.
Latent Class Models for Algorithm Portfolio Methods 2010
Bryan Silverthorn and Risto Miikkulainen, In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence 2010.
Learning a Hierarchy of Discriminative Space-Time Neighborhood Features for Human Action Recognition 2010
A. Kovashka and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010.
Learning for Semantic Parsing Using Statistical Syntactic Parsing Techniques 2010
Ruifang Ge, PhD Thesis, Department of Computer Science, University of Texas at Austin. 165 pages.
Learning Powerful Kicks on the Aibo ERS-7: The Quest for a Striker 2010
Matthew Hausknecht and Peter Stone, In Robocup International Symposium 2010.
Learning to Predict Readability using Diverse Linguistic Features 2010
Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan, Martin Franz, Radu Florian, Raymond J. Mooney, Salim Roukos and Chris Welty, In 23rd International Conference on Computational Linguistics (COLING 2010) 2010.
MARIOnET: Motion Acquisition for Robots through Iterative Online Evaluative Training 2010
Adam Setapen, Michael Quinlan, and Peter Stone, In Ninth International Conference on Autonomous Agents and Multiagent Systems - Agents Learning Interactively from Human Teachers Workshop (AAMAS - ALIHT), May 2010.
Message-passing for graph-structured linear programs: proximal methods and rounding schemes 2010
P. Ravikumar, A. Agarwal, and M. J. Wainwright, Journal of Machine Learning Research (JMLR), Vol. 11 (2010), pp. 1043-1080.
Motion Planning Algorithms for Autonomous Intersection Management 2010
Tsz-Chiu Au and Peter Stone, In AAAI 2010 Workshop on Bridging The Gap Between Task And Motion Planning (BTAMP) 2010.
Multi-Prototype Vector-Space Models of Word Meaning 2010
Joseph Reisinger, Raymond J. Mooney, In Proceedings of the 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-2010), pp. 109-117 2010.
Neuroevolution 2010
Risto Miikkulainen, In Encyclopedia of Machine Learning, New York 2010. Springer.
Object-Graphs for Context-Aware Category Discovery 2010
Y.J. Lee and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010.
On the Stable Model Semantics of First-Order Formulas with Aggregates 2010
Paolo Ferraris and Vladimir Lifschitz, In Proceedings of the 2010 Workshop on Nonmonotonic Reasoning 2010.
Online Max-Margin Weight Learning with Markov Logic Networks 2010
Tuyen N. Huynh and Raymond J. Mooney, In Proceedings of the AAAI-10 Workshop on Statistical Relational AI (Star-AI 10), pp. 32--37, Atlanta, GA, July 2010.
Online Model Learning in Adversarial Markov Decision Processes (Extended Abstract) 2010
Doran Chakraborty and Peter Stone, In Proceedings of the Ninth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 1583–-1584, May 2010.
Reading Between The Lines: Object Localization Using Implicit Cues from Image Tags 2010
S.J. Hwang and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2010.
Real Time Targeted Exploration in Large Domains 2010
Todd Hester and Peter Stone, In Proceedings of the Ninth International Conference on Development and Learning (ICDL 2010), 2010 (Eds.), August 2010.
Representing Synonymity in Causal Logic and in Logic Programming 2010
Joohyung Lee, Yuliya Lierler, Vladimir Lifschitz and Fangkai Yang, In Proceedings of International Workshop on Nonmonotonic Reasoning (NMR) 2010.
SAT-Based Answer Set Programming 2010
Yuliya Lierler, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Speciation in NEAT 2010
Timothy Nodine, Technical Report HR-10-06, Department of Computer Science, The University of Texas at Austin.
Spherical Topic Models 2010
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond J. Mooney, In Proceedings of the 27th International Conference on Machine Learning (ICML 2010) 2010.
Structured Exploration for Reinforcement Learning 2010
Nicholas Kenneth Jong, No other information
TacTex09: A Champion Bidding Agent for Ad Auctions 2010
David Pardoe, Doran Chakraborty, and Peter Stone, In Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2010), May 2010.
Thirteen Definitions of a Stable Model 2010
Vladimir Lifschitz, In Fields of Logic and Computation: Essays Dedicated to Yuri Gurevich on the Occasion of his 70th Birthday 2010.
Top-Down Pairwise Potentials for Piecing Together Multi-Class Segmentation Puzzles 2010
S. Vijayanarasimhan and K. Grauman, In The seventh IEEE Computer Society Workshop on Perceptual Organization in Computer Vision (POCV) 2010.
Towards the Object Semantic Hierarchy 2010
Changhai Xu and Benjamin Kuipers, In International Conference on Development and Learning (ICDL-10) 2010.
Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language 2010
David L. Chen, Joohyun Kim, Raymond J. Mooney, Journal of Artificial Intelligence Research, Vol. 37 (2010), pp. 397--435.
Transfer Learning for Reinforcement Learning on a Physical Robot 2010
Samuel Barrett, Matthew E. Taylor, and Peter Stone, In Ninth International Conference on Autonomous Agents and Multiagent Systems - Adaptive Learning Agents Workshop (AAMAS - ALA), May 2010.
Translating First-Order Causal Theories into Answer Set Programming 2010
Vladimir Lifschitz and Fangkai Yang, In Proceedings of the European Conference on Logics in Artificial Intelligence (JELIA) 2010.
Using Closed Captions as Supervision for Video Activity Recognition 2010
Sonal Gupta, Raymond J. Mooney, In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2010), pp. 1083--1088, Atlanta, GA, July 2010.
Utilizing Symmetry in Evolutionary Design 2010
Vinod Valsalam, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI-10-04.
Vision Calibration and Processing on a Humanoid Soccer Robot 2010
Piyush Khandelwal, Matthew Hausknecht, Juhyun Lee, Aibo Tian, and Peter Stone, In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, Nashville, TN 2010.
Knowledge integration across multiple texts 2009
Doo Soon Kim, Ken Barker, and Bruce Porter, In The Fifth International Conference on Knowledge Capture (KCAP2009) 2009.
3D pose estimation for planes 2009
Changhai Xu, Benjamin Kuipers, and Aniket Murarka, In ICCV Workshop on 3D Representation for Recognition (3dRR-09) 2009.
A Comparison of Strategies for Developmental Action Acquisition in QLAP 2009
Jonathan Mugan and Benjamin Kuipers, In Proceedings of the International Conference on Epigenetic Robotics (EpiRob-09), pp. 2009.
A framework for planning comfortable and customizable motion of an assistive mobile robot 2009
Shilpa Gulati, Chetan Jhurani, Benjamin Kuipers, and Raul Longoria, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2009.
A Modular Language for Describing Actions 2009
Wanwan Ren, PhD Thesis, University of Texas at Austin.
A Population Gain Control Model of Spatiotemporal Responses in the Visual Cortex 2009
Yiu Fai Sit, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. Technical Report AI09-06.
A Scalable Problem-Solver for Large Knowledge-Bases 2009
S. Chaw, K. Barker, B. Porter, D. Tecuci, and Peter Yeh, In Proceedings of the 21st International Conference on Tools with Artificial Intelligence (ICTAI 2009) 2009.
A stereo vision based 3D mapping algorithm for detecting ramps, drop-offs, and obstacles for safe local navigation 2009
Aniket Murarka and Benjamin Kuipers, In International Conference on Intelligent Robots and Systems (IROS) 2009.
A unified framework for high-dimensional analysis of M-estimators with decomposable regularizers 2009
S. Negahban, P. Ravikumar, M. J. Wainwright, and B. Yu, In Neural Information Processing Systems 2009.
Activity Retrieval in Closed Captioned Videos 2009
Sonal Gupta, Masters Thesis, Department of Computer Sciences, University of Texas at Austin. 64 pages.
An Empirical Analysis of Value Function-Based and Policy Search Reinforcement Learning 2009
Shivaram Kalyanakrishnan and Peter Stone, In The Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), pp. 749-756, Richland, SC, May 2009. International Foundation for Autonomous Agents and Multiagent Sy...
An Empirical Comparison of Abstraction in Models of Markov Decision Processes 2009
Todd Hester and Peter Stone, In Proceedings of the ICML/UAI/COLT Workshop on Abstraction in Reinforcement Learning, June 2009.
Autonomously Learning an Action Hierarchy Using a Learned Qualitative State Representation 2009
Jonathan Mugan and Benjamin Kuipers, In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-09) 2009.
Cognitive Task Analysis for Developing UAV Wilderness Search Support 2009
Julie A. Adams, Curtis M. Humphrey, Michael A. Goodrich, Joseph L. Cooper, Bryan S. Morse, Cameron Engh and Nathan Rasmussen, Journal of Cognitive Engineering and Decision Making, Vol. 3, 1 (2009), pp. 1--26.
Color Learning and Illumination Invariance on Mobile Robots: A Survey 2009
Mohan Sridharan and Peter Stone, Robotics and Autonomous Systems (RAS) Journal, Vol. 57, 60-7 (2009), pp. 629-44.
Complex Dynamics of V1 Population Responses Explained by a Simple Gain-Control Model 2009
Yiu Fai Sit, Yuzhi Chen, Wilson S. Geisler, Risto Miikkulainen, and Eyal Seidemann, Neuron, Vol. 64 (2009), pp. 943-956.
Compositional Models for Reinforcement Learning 2009
Nicholas K. Jong and Peter Stone, In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2009.
Computational Predictions on the Receptive Fields and Organization of V2 for Shape Processing 2009
Yiu Fai Sit and Risto Miikkulainen, Neural Computation, Vol. 21, 3 (2009), pp. 762--785.
Computer aided software design via inference and constraint propagation 2009
Gordon Novak, Integrated Computer-Aided Engineering, Vol. 16, 3 (2009), pp. 181-191.
Connectivity-based Localization in Robot Networks 2009
Tobias Jung, Mazda Ahmadi, and Peter Stone, In International Workshop on Robotic Wireless Sensor Networks (IEEE DCOSS '09), June 2009.
Constructing a semantic interpreter using distributional analysis 2009
Michael Glass, Ken Barker, Rekha Kumar, Guhan Ravi and Bruce Porter, In Proceedings of the Eighth Conference of the Pacific Association for Computational Linguistics 2009.
Construction of the Object Semantic Hierarchy 2009
Changhai Xu and Benjamin Kuipers, In Fifth International Cognitive Vision Workshop (ICVW-09) 2009.
Critical Factors in the Empirical Performance of Temporal Difference and Evolutionary Methods for Reinforcement Learning 2009
Shimon Whiteson, Matthew E. Taylor, and Peter Stone, Journal of Autonomous Agents and Multi-Agent Systems, Vol. 21, 1 (2009), pp. 1-27.
Design Principles for Creating Human-Shapable Agents 2009
W. Bradley Knox, Ian Fasel, and Peter Stone, In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2009.
Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study 2009
W. Bradley Knox and Ole Mengshoel, In IJCAI 2009 Workshop on Self-* and Autonomous Systems 2009.
Discriminative Learning with Markov Logic Networks 2009
Tuyen N. Huynh, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Evolving Adaptive Intelligence: Using NeuroEvolution with Temporal Difference Methods in the Game Domain 2009
Nathaniel Tucker, Technical Report HR-09-04, Department of Computer Science, The University of Texas at Austin..
Evolving Multi-modal Behavior in NPCs 2009
Jacob Schrum and Risto Miikkulainen, In IEEE Symposium on Computational Intelligence and Games (CIG 2009), pp. 325--332, Milan, Italy, September 2009. (Best Student Paper Award).
Evolving Neural Networks for Strategic Decision-Making Problems 2009
Nate Kohl and Risto Miikkulainen, Neural Networks, Special issue on Goal-Directed Neural Systems (2009).
Evolving Symmetric and Modular Neural Network Controllers for Multilegged Robots 2009
Vinod K. Valsalam and Risto Miikkulainen, In xploring New Horizons in Evolutionary Design of Robots: Workshop at the 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2009.
Evolving Symmetric and Modular Neural Networks for Distributed Control 2009
Vinod K. Valsalam and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 731--738 2009.
Feature Selection for Value Function Approximation Using Bayesian Model Selection 2009
Tobias Jung and Peter Stone, In The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, September 2009.
Generalized Domains for Empirical Evaluations in Reinforcement Learning 2009
Shimon Whiteson, Brian Tanner, Matthew E. Taylor, and Peter Stone, In ICML Workshop on Evaluation Methods for Machine Learning, June 2009. To appear..
Generalized Model Learning for Reinforcement Learning in Factored Domains 2009
Todd Hester and Peter Stone, In The Eighth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2009.
Hyperlearning: A Connectionist Model of Psychosis in Schizophrenia 2009
Uli Grasemann, Risto Miikkulainen and Ralph Hoffman, In Proceedings of the 31st Annual Meeting of the Cognitive Science Society, N. A. Taatgen and H. van Rijn (Eds.), Amsterdam, The Netherlands 2009.
Improving Particle Filter Performance Using SSE Instructions 2009
Peter Djeu, Michael Quinlan, and Peter Stone, In Proceedings of IROS 2009: 2009 IEEE/RSJ International Conference on Intelligent RObots and Systems, October 2009.
Information-theoretic lower bounds on the oracle complexity of convex optimization 2009
A. Agarwal, P. Bartlett, P. Ravikumar, and M. Wainwright, In Neural Information Processing Systems 2009.
Interactively Shaping Agents via Human Reinforcement: The TAMER Framework 2009
W. Bradley Knox and Peter Stone, In The Fifth International Conference on Knowledge Capture, September 2009.
Kernelized Locality-Sensitive Hashing for Scalable Image Search 2009
B. Kulis and K. Grauman, In IEEE International Conference on Computer Vision (ICCV) 2009.
Kleo: A Bootstrapping Learning-by-reading System 2009
Doo Soon Kim and Bruce Porter, In AAAI Spring Symposium on Learning by Reading and Learning to Read 2009.
Leading a Best-Response Teammate in an Ad Hoc Team 2009
Peter Stone, Gal A. Kaminka, and Jeffrey S. Rosenschein, In {AAMAS} Workshop on Agent Mediated Electronic Commerce, pp. 153-167, May 2009.
Learning a Compositional Semantic Parser using an Existing Syntactic Parser 2009
Ruifang Ge and Raymond J. Mooney, In Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of ...
Learning Complementary Multiagent Behaviors: A Case Study 2009
Shivaram Kalyanakrishnan and Peter Stone, In Proceedings of the RoboCup International Symposium 2009 2009. Springer Verlag.
Learning Dynamic Obstacle Avoidance for a Robot Arm Using Neuroevolution 2009
Thomas D'Silva, Risto Miikkulainen, Neural Processing Letters (2009).
Learning in Fractured Problems for Constructive Neural Network Algorithms 2009
Nate Kohl, PhD Thesis, Department of Computer Sciences, University of Texas at Austin.
Learning Language from Perceptual Context 2009
David L. Chen, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Learning the Sensorimotor Structure of the Foveated Retina 2009
Jeremy Stober, Lewis Fishgold, and Benjamin Kuipers, In Proceedings of the Ninth International Conference on Epigenetic Robotics 2009.
Learning to Disambiguate Search Queries from Short Sessions 2009
Lilyana Mihalkova and Raymond Mooney, In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Part 2, pp. 111--127, Bled, Slovenia, September 2009.
Learning with Markov Logic Networks: Transfer Learning, Structure Learning, and an Application to Web Query Disambiguation 2009
Lilyana Mihalkova, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 176 pages.
Max-Margin Weight Learning for Markov Logic Networks 2009
Tuyen N. Huynh and Raymond J. Mooney, In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Part 1, pp. 564--579, Bled, Slovenia, September 2009.
Max-Margin Weight Learning for Markov Logic Networks 2009
Tuyen N. Huynh and Raymond J. Mooney, In Proceedings of the International Workshop on Statistical Relational Learning (SRL-09), Leuven, Belgium, July 2009.
Modeling the Bilingual Lexicon of an Individual Subject 2009
Risto Miikkulainen and Swathi Kiran, In Proceedings of the Workshop on Self-Organizing Maps (WSOM'09), Berlin 2009. Springer.
Navigation, Control and Recovery of the ENDURANCE Under-ice Hovering AUV 2009
Kristof Richmond, Shilpa Gulati, Chris Flesher, Bartholomew P. Hogan, and William C. Stone, In International Symposium on Unmanned Untethered Submersible Technology (UUST) 2009.
Observe Locally, Infer Globally: a Space-Time MRF for Detecting Abnormal Activities with Incremental Updates 2009
Jaechul Kim and Kristen Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2009.
One More Decidable Class of Finitely Ground Programs 2009
Yuliya Lierler and Vladimir Lifschitz, In Proc. International Conference on Logic Programming (ICLP) 2009.
Probabilistic Abduction using Markov Logic Networks 2009
Rohit J. Kate and Raymond J. Mooney, In Proceedings of the IJCAI-09 Workshop on Plan, Activity, and Intent Recognition (PAIR-09), Pasadena, CA, July 2009.
Semi-supervised graph clustering: a kernel approach 2009
Brian Kulis, Sugato Basu, Inderjit Dhillon, and Raymond Mooney, Machine Learning Journal, Vol. 74, 1 (2009), pp. 1-22.
Sensor Map Discovery for Developing Robots 2009
Jeremy Stober, Lewis Fishgold, and Benjamin Kuipers, In AAAI Fall Symposia Series: Manifold Learning and Its Applications 2009. Appears in AAAI Technical Report FS-09-04..
Shape Discovery from Unlabeled Image Collections 2009
Y. J. Lee and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2009.
Skill Reuse in Lifelong Developmental Learning 2009
Jonathan Mugan and Benjamin Kuipers, In IROS 2009 Workshop: Autonomous Mental Development for Intelligent Robots and Systems, pp. 2009.
Sparse Additive Models 2009
P. Ravikumar, J. Lafferty, H. Liu, and L. Wasserman, Journal of the Royal Statistical Society: Series B (Statistical Methodology) (JRSSB), Vol. 71, 5 (2009), pp. 1009-1030.
Speeding up Inference In Statistical Relational Learning by Clustering Similar Query Literals 2009
Lilyana Mihalkova and Matthew Richardson, In Proceedings of the 19th International Conference on Inductive Logic Programming (ILP-09), Leuven, Belgium, July 2009.
Spherical Topic Models 2009
Joseph Reisinger, Austin Waters, Bryan Silverthorn, and Raymond Mooney, In NIPS'09 workshop: Applications for Topic Models: Text and Beyond 2009.
Sub-ice exploration of West Lake Bonney: ENDURANCE 2008 Mission 2009
Bill Stone, Bart Hogan, Chris Flesher, Shilpa Gulati, Kristof Richmond, Aniket Murarka, Gregory Kuhlmann, and Mohan Sridharan, In International Symposium on Unmanned Untethered Submersible Technology (UUST) 2009.
Symmetric Splitting in the General Theory of Stable Models 2009
Paolo Ferraris, Joohyung Lee, Vladimir Lifschitz, and Ravi Palla, In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 797-803 2009.
Temporal Convolution Machines for Sequence Learning 2009
Alan J Lockett and Risto Miikkulainen, Technical Report AI-09-04, Department of Computer Sciences, the University of Texas at Austin.
The Necessity of Separating Control and Logic When Grounding Language Using Neuroevolution 2009
Yonatan Bisk, Technical Report HR-09-05, Department of Computer Sciences, The University of Texas at Austin.
The UT Austin Villa 3D Simulation Soccer Team 2008 2009
Shivaram Kalyanakrishnan, Yinon Bentor, and Peter Stone, Technical Report AI09-01, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Three Humanoid Soccer Platforms: Comparison and Synthesis 2009
Shivaram Kalyanakrishnan, Todd Hester, Michael Quinlan, Yinon Bentor, and Peter Stone, In Proceedings of the RoboCup International Symposium 2009 2009. Springer Verlag.
Towards a Safe, Low-Cost, Intelligent Wheelchair 2009
Aniket Murarka, Shilpa Gulati, Patrick Beeson, and Benjamin Kuipers, In Workshop on Planning, Perception and Navigation for Intelligent Vehicles (PPNIV) 2009.
Towards using Unmanned Aerial Vehicles (UAVs) in Wilderness Search and Rescue: Lessons from field trials 2009
Michael A. Goodrich, Bryan S. Morse, Cameron Engh, Joseph L. Cooper and Julie A. Adams, Interaction Studies, Vol. 10, 3 (2009), pp. 455--481.
Transfer Learning for Reinforcement Learning Domains: A Survey 2009
Matthew E. Taylor and Peter Stone, Journal of Machine Learning Research, Vol. 10, 1 (2009), pp. 1633-1685.
Transfer Learning from Minimal Target Data by Mapping across Relational Domains 2009
Lilyana Mihalkova and Raymond Mooney, In Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 1163--1168, Pasadena, CA, July 2009.
TT-UT Austin Villa 2009: Naos across Texas 2009
Todd Hester, Michael Quinlan, Peter Stone, and Mohan Sridharan, Technical Report UT-AI-TR-09-08, The University of Texas at Austin, Department of Computer Science, AI Laboratory.
Using Closed Captions to Train Activity Recognizers that Improve Video Retrieval 2009
Sonal Gupta and Raymond Mooney, In Proceedings of the CVPR-09 Workshop on Visual and Contextual Learning from Annotated Images and Videos (VCL), Miami, FL, June 2009.
Vision based frozen surface egress: A docking algorithm for the ENDURANCE AUV 2009
Aniket Murarka, Gregory Kuhlmann, Shilpa Gulati, Mohan Sridharan, Chris Flesher, and Bill Stone, In International Symposium on Unmanned Untethered Submersible Technology (UUST) 2009.
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations 2009
S. Vijayanarasimhan and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2009.
A Library of General-Purpose Action Descriptions 2008
Selim T. Erdoğan, PhD Thesis, Computer Sciences Department, The University of Texas at Austin.
A Dependency-based Word Subsequence Kernel 2008
Rohit J. Kate, In Proceedings of the conference on Empirical Methods in Natural Language Processing (EMNLP-2008), pp. 400--409, Waikiki, Honolulu, Hawaii, October 2008.
A General Purpose Task Specification Language for Bootstrap Learning 2008
Ian Fasel, Michael Quinlan, and Peter Stone, In AAAI Spring 2009 Symposium on Agents that Learn from Human Teachers, March 2008.
A Multiagent Approach to Autonomous Intersection Management 2008
Kurt Dresner and Peter Stone, Journal of Artificial Intelligence Research, Vol. 31 (2008), pp. 591-656.
A Neural Network-Based Approach to Robot Motion Control 2008
Uli Grasemann, Daniel Stronger, and Peter Stone, In RoboCup-2007: Robot Soccer World Cup XI, Ubbo Visser and Fernando Ribeiro and Takeshi Ohashi and Frank Dellaert (Eds.), Vol. 5001, pp. 480-87, Berlin 2008. Springer Verlag.
A Reductive Semantics for Counting and Choice in Answer Set Programming 2008
Joohyung Lee, Vladimir Lifschitz, and Ravi Palla, In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp. 472-479 2008.
Abstract Answer Set Solvers 2008
Yuliya Lierler, In Proceedings of International Conference on Logic Programming (ICLP'08), pp. 377-391 2008. Springer.
Accelerated Neural Evolution through Cooperatively Coevolved Synapses 2008
Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen, Journal of Machine Learning Research (2008), pp. 937-965.
Autonomous Transfer for Reinforcement Learning 2008
Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone, In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
Category Learning Systems 2008
Dagmar Zeithamova, PhD Thesis, Institute for Neuroscience, The University of Texas at Austin.
Competition Between Reinforcement Learning Methods in a Predator-Prey Grid World 2008
Jacob Schrum, Technical Report AI08-9, The University of Texas at Austin, Department of Computer Sciences.
Constructing Complex NPC Behavior via Multi-Objective Neuroevolution 2008
Jacob Schrum and Risto Miikkulainen, In Proceedings of the Fourth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2008), pp. 108-113, Stanford, California 2008.
Continuous-domain reinforcement learning using a learned qualitative state representation 2008
Jonathan Mugan and Benjamin Kuipers, In 22nd International Workshop on Qualitative Reasoning (QR-08) 2008.
Coupling Data Understanding with Software Reuse 2008
Gordon Novak, In IEEE International Conference on Information Reuse and Integration (IRI-2008), pp. 110-115, Las Vegas NV 2008.
Creating and Utilizing Symbolic Representations of Spatial Knowledge using Mobile Robots 2008
Patrick Beeson, PhD Thesis, Computer Sciences Department, The University of Texas at Austin.
Detecting obstacles and drop-offs using stereo and motion cues for safe local motion 2008
Aniket Murarka, Mohan Sridharan and Benjamin Kuipers, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-08) 2008.
Discriminative Structure and Parameter Learning for Markov Logic Networks 2008
Tuyen N. Huynh and Raymond J. Mooney, In Proceedings of the 25th International Conference on Machine Learning (ICML), Helsinki, Finland, July 2008.
Dissociable prototype learning systems: Evidence from brain imaging and behavior 2008
Dagmar Zeithamova, W. Todd Maddox and David M. Schnyer, Journal of Neuroscience, Vol. 28, 49 (2008), pp. 13194-13201.
Evolving Controllers for Simulated Car Racing using Neuroevolution 2008
Aravind Gowrisankar, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 85 pages.
Evolving Neural Networks for Fractured Domains 2008
Nate Kohl and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1405-1412, July 2008.
Evolving Opponent Models for Texas Hold 'Em 2008
Alan J Lockett and Risto Miikkulainen, In IEEE Conference on Computational Intelligence in Games, Perth, Australia 2008.
Fast Image Search for Learned Metrics 2008
P. Jain, B. Kulis, and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2008.
Foreground Focus: Finding Meaningful Features in Unlabeled Images 2008
Y. J. Lee and K. Grauman, In British Machine Vision Conference (BMVC) 2008.
From pixels to policies: a bootstrapping agent 2008
Jeremy Stober and Benjamin Kuipers, In Proceedings of the IEEE International Conference on Development and Learning 2008.
Hierarchical Model-Based Reinforcement Learning: Rmax + MAXQ 2008
Nicholas K. Jong and Peter Stone, In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
High Performance Control for Graceful Motion of an Intelligent Wheelchair 2008
Shilpa Gulati and Benjamin Kuipers, In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2008.
Improving semantic integration by learning semantic interpretation rules 2008
Michael Glass and Bruce Porter, In AAAI Spring Symposium on Semantic Scientific Knowledge Integration 2008.
Incremental Nonmonotonic Sentence Interpretation through Semantic Self-Organization 2008
Marshall R. Mayberry III and Risto Miikkulainen, Technical Report AI08-12, Department of Computer Sciences, University of Texas at Austin.
Instance-Based Action Models for Fast Action Planning 2008
Mazda Ahmadi and Peter Stone, In RoboCup-2007: Robot Soccer World Cup XI, Ubbo Visser and Fernando Ribeiro and Takeshi Ohashi and Frank Dellaert (Eds.), Vol. 5001, pp. 1-16, Berlin 2008. Springer Verlag.
Integrating declarative knowledge: Issues, Algorithms and Future Work 2008
Doo Soon Kim and Bruce Porter, In AAAI Spring Symposium on Semantic Scientific Knowledge Integration 2008.
Inter-Classifier Feedback for Human-Robot Interaction in a Domestic Setting 2008
Juhyun Lee, W. Bradley Knox, and Peter Stone, Journal of Physical Agents, Vol. 2, 2 (2008), pp. 41-50. Special Issue on Human Interaction with Domestic Robots.
Keywords to Visual Categories: Multiple-Instance Learning for Weakly Supervised Object Categorization 2008
S. Vijayanarasimhan and K. Grauman, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2008.
Knowledge Representation and Classical Logic 2008
Vladimir Lifschitz, Leora Morgenstern and David Plaisted, In Handbook of Knowledge Representation, Frank van Harmelen and Vladimir Lifschitz and Bruce Porter (Eds.), pp. 3-88 2008. Elsevier.
Knowledge Representation and Question Answering 2008
Marcello Balduccini, Chitta Baral, Yuliya Lierler, In Handbook of Knowledge Representation, Frank van Harmelen and Vladimir Lifschitz and Bruce Porter (Eds.), pp. 779-820 2008. Elsevier.
Learning to Connect Language and Perception 2008
Raymond J. Mooney, In Proceedings of the 23rd AAAI Conference on Artificial Intelligence (AAAI), pp. 1598--1601, Chicago, IL, July 2008. Senior Member Paper.
Learning to Sportscast: A Test of Grounded Language Acquisition 2008
David L. Chen and Raymond J. Mooney, In Proceedings of the 25th International Conference on Machine Learning (ICML), Helsinki, Finland, July 2008.
Maximum Likelihood Estimation of Sensor and Action Model Functions on a Mobile Robot 2008
Daniel Stronger and Peter Stone, In IEEE International Conference on Robotics and Automation, May 2008.
Memory Processes in Perceptual Decision Making 2008
Manish Saggar, Risto Miikkulainen, David M Schnyer, In Proceedings of the 30th Annual Conference of the Cognitive Science Society, Nashville, TN 2008.
Message-passing for graph-structured linear programs: Proximal projections, convergence and rounding schemes 2008
P. Ravikumar, A. Agarwal, and M. J. Wainwright, In International Conference on Machine learning (ICML) 2008.
Mitigating Catastrophic Failure at Intersections of Autonomous Vehicles 2008
Kurt Dresner and Peter Stone, In AAMAS Workshop on Agents in Traffic and Transportation, pp. 78-85, Estoril, Portugal, May 2008.
Model selection in Gaussian graphical models: High-dimensional consistency of l1-regularized MLE 2008
P. Ravikumar, M. J. Wainwright, G. Raskutti, and B. Yu, In Neural Information Processing Systems 2008.
Model-based Reinforcement Learning in a Complex Domain 2008
Shivaram Kalyanakrishnan, Peter Stone, and Yaxin Liu, In RoboCup-2007: Robot Soccer World Cup XI, Ubbo Visser and Fernando Ribeiro and Takeshi Ohashi and Frank Dellaert (Eds.), Vol. 5001, pp. 171-83, Berlin 2008. Springer Verlag.
Modular Neuroevolution for Multilegged Locomotion 2008
Vinod K. Valsalam and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference GECCO 2008, pp. 265-272, New York, NY, USA 2008. ACM.
Motion Perception and the Scene Statistics of Motion 2008
Tal Tversky, PhD Thesis, Department of Computer Science, The University of Texas at Austin.
Multi-Level Active Prediction of Useful Image Annotations for Recognition 2008
S. Vijayanarasimhan and K. Grauman, In Advances in Neural Information Processing Systems (NIPS) 2008.
Multiagent Interactions in Urban Driving 2008
Patrick Beeson, Jack O'Quin, Bartley Gillan, Tarun Nimmagadda, Mickey Ristroph, David Li, and Peter Stone, Journal of Physical Agents, Vol. 2, 1 (2008), pp. 15-30. Special issue on Multi-Robot Systems.
Negative Information and Line Observations for Monte Carlo Localization 2008
Todd Hester and Peter Stone, In IEEE International Conference on Robotics and Automation, May 2008.
Nonparametric sparse hierarchical models describe V1 fmri responses to natural images 2008
P. Ravikumar, V. Vu, B. Yu, T. Naselaris, K. Kay, and J. Gallant, In Neural Information Processing Systems 2008.
Online Kernel Selection for Bayesian Reinforcement Learning 2008
Joseph Reisinger, Peter Stone, and Risto Miikkulainen, In Proceedings of the Twenty-Fifth International Conference on Machine Learning, July 2008.
Online Metric Learning and Fast Similarity Search 2008
P. Jain, B. Kulis, I. Dhillon, and K. Grauman, In Advances in Neural Information Processing Systems (NIPS) 2008.
Online Multiagent Learning against Memory Bounded Adversaries 2008
Doran Chakraborty and Peter Stone, In Machine Learning and Knowledge Discovery in Databases, Vol. 5212, pp. 211-26, September 2008.
Polynomial Regression with Automated Degree: A Function Approximator for Autonomous Agents 2008
Daniel Stronger and Peter Stone, International Journal on Artificial Intelligence Tools, Vol. 17, 1 (2008), pp. 159-174.
Ray-based color image segmentation 2008
Changhai Xu, Yong Jae Lee, and Benjamin Kuipers, In Canadian Conference on Computer and Robot Vision 2008.
Replacing the Stop Sign: Unmanaged Intersection Control for Autonomous Vehicles 2008
Mark VanMiddlesworth, Kurt Dresner, and Peter Stone, In AAMAS Workshop on Agents in Traffic and Transportation, pp. 94-101, Estoril, Portugal, May 2008.
Safe Formulas in the General Theory of Stable Models (preliminary report) 2008
Joohyung Lee, Vladimir Lifschitz, and Ravi Palla, In International Conference on Logic Programming (ICLP) 2008.
Search Query Disambiguation from Short Sessions 2008
Lilyana Mihalkova and Raymond Mooney, In Beyond Search: Computational Intelligence for the Web Workshop at NIPS 2008.
Supporting Flight Control for UAV-Assisted Wilderness Search and Rescue Through Human Centered Interface Design 2008
Joseph L. Cooper, Masters Thesis, Brigham Young University.
Supporting Wilderness Search and Rescue using a Camera-Equipped Mini UAV 2008
Michael A. Goodrich, Bryan S. Morse, Damon Gerhardt, Joseph L. Cooper, Morgan Quigley, Julie A. Adams and Curtis Humphrey, Journal of Field Robotics, Vol. 25, 1--2 (2008), pp. 89--110.
The 2007 TAC SCM Prediction Challenge 2008
David Pardoe and Peter Stone, In AAAI 2008 Workshop on Trading Agent Design and Analysis 2008.
The Utility of Temporal Abstraction in Reinforcement Learning 2008
Nicholas K. Jong, Todd Hester, and Peter Stone, In The Seventh International Joint Conference on Autonomous Agents and Multiagent Systems, May 2008.
Towards Combining UAV and Sensor Operator Roles in UAV-Enabled Visual Search 2008
Joseph L. Cooper and Michael A. Goodrich, In Proceedings of ACM/IEEE International Conference on Human-Robot Interaction, Amsterdam, The Netherlands, March 2008.
Towards the Application of Reinforcement Learning to Undirected Developmental Learning 2008
Jonathan Mugan and Benjamin Kuipers, In Proceedings of the International Conference on Epigenetic Robotics (EpiRob-08) 2008.
Trajectory generation for dynamic bipedal walking through qualitative model based manifold learning 2008
Subramanian Ramamoorthy and Benjamin Kuipers, In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA-08) 2008.
Transfer Learning and Intelligence: an Argument and Approach 2008
Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone, In Proceedings of the First Conference on Artificial General Intelligence, March 2008.
Transfer Learning by Mapping with Minimal Target Data 2008
Lilyana Mihalkova and Raymond J. Mooney, Proceedings of the AAAI-08 Workshop on Transfer Learning For Complex Tasks (2008).
Transfer of Evolved Pattern-Based Heuristics in Games 2008
Erkin Bahceci and Risto Miikkulainen, In IEEE Symposium On Computational Intelligence and Games (CIG 2008), pp. 220-227, Perth, Australia, December 2008.
Transferring Instances for Model-Based Reinforcement Learning 2008
Matthew E. Taylor, Nicholas K. Jong, and Peter Stone, In Machine Learning and Knowledge Discovery in Databases, Vol. 5212, pp. 488-505, September 2008.
Transforming Meaning Representation Grammars to Improve Semantic Parsing 2008
Rohit J. Kate, In Proceedings of the Twelfth Conference on Computational Natural Language Learning (CoNLL-2008), pp. 33--40, Manchester, UK, August 2008.
Twelve Definitions of a Stable Model 2008
Vladimir Lifschitz, In Proceedings of International Conference on Logic Programming (ICLP), pp. 37-51 2008.
UT Austin Villa 2008: Standing on Two Legs 2008
Todd Hester, Michael Quinlan, and Peter Stone, Technical Report UT-AI-TR-08-8, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Watch, Listen & Learn: Co-training on Captioned Images and Videos 2008
Sonal Gupta, Joohyun Kim, Kristen Grauman and Raymond Mooney, In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 457--472, Antwerp Belgium, September 2008.
What Is Answer Set Programming? 2008
Vladimir Lifschitz, In Proceedings of the AAAI Conference on Artificial Intelligence, pp. 1594-1597 2008. MIT Press.
A Characterization of Strong Equivalence for Logic Programs with Variables 2007
Vladimir Lifschitz, David Pearce and Agustin Valverde, In Procedings of International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR) 2007.
A Comparison of Two Approaches for Vision and Self-Localization on a Mobile Robot 2007
Daniel Stronger and Peter Stone, In IEEE International Conference on Robotics and Automation, pp. 3915-3920, April 2007.
A computational model of the motivation-learning interface 2007
Manish Saggar, Arthur B Markman, W Todd Maddox, Risto Miikkulainen, In Proceedings of the 29th Annual Conference of the Cognitive Science Society, Nashville, TN 2007.
A Computational Model of the Signals in Optical Imaging with Voltage-Sensitive Dyes 2007
Yiu Fai Sit and Risto Miikkulainen, Neurocomputing (2007), pp. 1853-1857.
A Logic Program Characterization of Causal Theories 2007
Paolo Ferraris, In IJCAI 2007.
A New Perspective on Stable Models 2007
Paolo Ferraris, Joohyung Lee and Vladimir Lifschitz, In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 372-379 2007.
A Subsymbolic Model of Language Pathology in Schizophrenia 2007
Uli Grasemann, Risto Miikkulainen, Ralph Hoffman, In Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 311-316, Hillsdale, NJ 2007. Erlbaum.
Accelerating Search with Transferred Heuristics 2007
Matthew E. Taylor, Gregory Kuhlmann, and Peter Stone, In ICAPS-07 workshop on AI Planning and Learning, September 2007.
Acquiring Evolvability through Adaptive Representations 2007
Joseph Reisinger and Risto Miikkulainen, In Proceeedings of the Genetic and Evolutionary Computation Conference, pp. 1045-1052 2007.
Acquiring Visibly Intelligent Behavior with Example-Guided Neuroevolution 2007
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the Twenty-Second National Conference on Artificial Intelligence, Menlo Park, CA 2007. AAAI Press.
Action Selection for Illumination Invariant Color Learning 2007
Mohan Sridharan and Peter Stone, In The IEEE International Conference on Intelligent Robots and Systems (IROS) 2007.
Active Learning with Gaussian Processes for Object Categorization 2007
A. Kapoor, K. Grauman, R. Urtasun, and T. Darrell, In IEEE International Conference on Computer Vision (ICCV) 2007.
Adapting Price Predictions in TAC SCM 2007
David Pardoe and Peter Stone, In AAMAS 2007 Workshop on Agent Mediated Electronic Commerce 2007.
Adaptive Tile Coding for Value Function Approximation 2007
Shimon Whiteson, Matthew E. Taylor, and Peter Stone, Technical Report AI-TR-07-339, University of Texas at Austin.
An Autonomous Agent for Supply Chain Management 2007
David Pardoe and Peter Stone, In Handbooks in Information Systems Series: Business Computing, Gedas Adomavicius and Alok Gupta (Eds.), Vol. 3, pp. 141-72 2007. Emerald Group.
Approximate Correspondences in High Dimensions 2007
K. Grauman and T. Darrell, In Advances in Neural Information Processing Systems 19 (NIPS) 2007.
Approximate inference, structure learning and feature estimation in Markov random fields 2007
P. Ravikumar, Technical Report CMU-ML-07-115, Ph.D. Thesis, Carnegie Mellon University (2007).
Autonomous Bidding Agents: Strategies and Lessons from the Trading Agent Competition 2007
Michael P. Wellman, Amy Greenwald, and Peter Stone, No other information
Autonomous Development of a Grounded Object Ontology by a Learning Robot 2007
Joseph Modayil and Benjamin Kuipers, In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI-07) 2007.
Autonomous Learning of Stable Quadruped Locomotion 2007
Manish Saggar, Thomas D'Silva, Nate Kohl, and Peter Stone, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), Vol. 4434, pp. 98-109, Berlin 2007. Springer Verlag.
Autonomous Return on Investment Analysis of Additional Processing Resources 2007
Jonathan Wildstrom, Peter Stone, and Emmett Witchel, In 2007 Workshop on Adaptive Methods in Autonomic Computing Systems, June 2007.
Batch Reinforcement Learning in a Complex Domain 2007
Shivaram Kalyanakrishnan and Peter Stone, In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 650-657, New York, NY, USA, May 2007. ACM.
Bottom-Up Learning of Markov Logic Network Structure 2007
Lilyana Mihalkova and Raymond J. Mooney, In Proceedings of 24th International Conference on Machine Learning (ICML-2007), Corvallis, OR, June 2007.
Cmodels: SAT-based Answer Set Programming System 2007
Yuliya Lierler and Marco Maratea, In ALP Newsletter 2007.
Coevolution of Role-Based Cooperation in Multi-Agent Systems 2007
Chern Han Yong and Risto Miikkulainen, Technical Report AI07-338, Department of Computer Sciences, The University of Texas at Austin.
Coevolving Strategies for General Game Playing 2007
Joseph Reisinger, Erkin Bahceci, Igor Karpov and Risto Miikkulainen, In Proceedings of the {IEEE} Symposium on Computational Intelligence and Games, pp. 320-327, Piscataway, NJ 2007. IEEE.
Color Learning on a Mobile Robot: Towards Full Autonomy under Changing Illumination 2007
Mohan Sridharan and Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 2212-2217, January 2007.
Cross-Domain Transfer for Reinforcement Learning 2007
Matthew E. Taylor and Peter Stone, In Proceedings of the Twenty-Fourth International Conference on Machine Learning, June 2007.
DARPA Urban Challenge Technical Report: Austin Robot Technology 2007
Peter Stone, Patrick Beeson, Tekin Mericli, and Ryan Madigan, Available from http://www.darpa.mil/grandchallenge/rules.asp.
Detecting Motion in the Environment with a Moving Quadruped Robot 2007
Peggy Fidelman, Thayne Coffman and Risto Miikkulainen, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), pp. 219-231, Berlin 2007. Springer Verlag.
Developing Complex Systems Using Evolved Pattern Generators 2007
Vinod K. Valsalam, James A. Bednar and Risto Miikkulainen, IEEE Transactions on Evolutionary Computation (2007), pp. 181-198.
Effects of Acquisition Rate on Emergent Structure in Phonological Development 2007
Melissa A. Redford and Risto Miikkulainen, Language (2007), pp. 737-769.
Empirical Studies in Action Selection for Reinforcement Learning 2007
Shimon Whiteson, Matthew E. Taylor, and Peter Stone, Adaptive Behavior, Vol. 15, 1 (2007), pp. 33-50.
Evolving Explicit Opponent Models for Game Play 2007
Alan Lockett, Charles Chen, and Risto Miikkulainen, In Genetic and Evolutionary Computation Conference (GECCO-2007) 2007.
Expressiveness of Answer Set Languages 2007
Paolo Ferraris, PhD Thesis, Computer Sciences Department, The University of Texas at Austin.
Extracting Relations from Text: From Word Sequences to Dependency Paths 2007
Razvan C. Bunescu and Raymond J. Mooney, In Natural Language Processing and Text Mining, A. Kao and S. Poteet (Eds.), pp. 29-44, Berlin 2007. Springer Verlag.
Following Natural Language Route Instructions 2007
Matthew T. MacMahon, PhD Thesis, Electrical and Computer Engineering Department, University of Texas at Austin.
General Game Learning using Knowledge Transfer 2007
Bikramjit Banerjee and Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 672-677, January 2007.
Generation by Inverting a Semantic Parser That Uses Statistical Machine Translation 2007
Yuk Wah Wong and Raymond J. Mooney, In Proceedings of Human Language Technologies: The Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT-07), pp. 172-179, Rochester, NY 2007.
Graph-Based Domain Mapping for Transfer Learning in General Games 2007
Gregory Kuhlmann and Peter Stone, In Proceedings of the 18th European Conference on Machine Learning, September 2007.
Half Field Offense in RoboCup Soccer: A Multiagent Reinforcement Learning Case Study 2007
Shivaram Kalyanakrishnan, Yaxin Liu, and Peter Stone, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), Vol. 4434, pp. 72-85, Berlin 2007. Springer Verlag.
Handling Granularity Differences in Knowledge Integration 2007
Doo Soon Kim and Bruce Porter, In AAAI Fall Symposium on Computational Approaches to Representation Change during Learning and Development 2007.
Head-Elementary-Set-Free Logic Programs 2007
Martin Gebser, Joohyung Lee, and Yuliya Lierler, In Logic Programming and Nonmonotonic Reasoning, pp. 149--161 2007.
IFSA: Incremental Feature-Set Augmentation for Reinforcement Learning Tasks 2007
Mazda Ahmadi, Matthew E. Taylor, and Peter Stone, In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
Improving Learning of Markov Logic Networks using Transfer and Bottom-Up Induction 2007
Lilyana Mihalkova, Technical Report UT-AI-TR-07-341, Artificial Intelligence Lab, University of Texas at Austin.
Inferring Phylogenetic Trees Using Answer Set Programming 2007
Daniel R. Brooks, Esra Erdem, Selim T. Erdogan, James W. Minett, and Donald Ringe, Journal of Automated Reasoning, Vol. 39 (2007), pp. 471-511.
Integrating Multiple Representations of Spatial Knowledge for Mapping, Navigation, and Communication 2007
Patrick Beeson, Matt MacMahon, Joseph Modayil, Aniket Murarka, Benjamin Kuipers, and Brian Stankiewicz, In AAAI Spring Symposium Series, Interaction Challenges for Intelligent Assistants 2007. AAAI Technical Report SS-07-04.
Intelligent Autonomous Robotics: A Robot Soccer Case Study 2007
Peter Stone, No other information
Learning and Multiagent Reasoning for Autonomous Agents 2007
Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 13-30, January 2007.
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned 2007
Ken Barker, Bhalchandra Agashe, Shaw-Yi Chaw, James Fan, Noah Friedland, Michael Glass, Jerry Hobbs, Eduard Hovy, David Israel, Doo Soon Kim, Rutu Mulkar-Mehta, Sourabh Patwardhan, Bruce Porter, Dan Tecuci, and Peter Yeh, In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI 2007) 2007.
Learning distinctions and rules in a continuous world through active exploration 2007
Jonathan Mugan and Benjamin Kuipers, In Proceedings of the International Conference on Epigenetic Robotics (EpiRob-07) 2007.
Learning for Information Extraction: From Named Entity Recognition and Disambiguation To Relation Extraction 2007
Razvan Constantin Bunescu, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 150 pages. Also as Technical Report AI07-345, Artificial Intelligence Lab, University of Texas at Austin, August 2007.
Learning for Semantic Parsing 2007
Raymond J. Mooney, In Computational Linguistics and Intelligent Text Processing: Proceedings of the 8th International Conference (CICLing 2007), A. Gelbukh (Eds.), pp. 311--324, Mexico City, Mexico, February 2007...
Learning for Semantic Parsing and Natural Language Generation Using Statistical Machine Translation Techniques 2007
Yuk Wah Wong, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 188 pages. Also appears as Technical Report AI07-343, Artificial Intelligence Lab, University of Texas at Austin, August 200...
Learning for Semantic Parsing with Kernels under Various Forms of Supervision 2007
Rohit J. Kate, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 159 pages.
Learning Language Semantics from Ambiguous Supervision 2007
Rohit J. Kate and Raymond J. Mooney, In Proceedings of the 22nd Conference on Artificial Intelligence (AAAI-07), pp. 895-900, Vancouver, Canada, July 2007.
Learning Policy Selection for Autonomous Intersection Management 2007
Kurt Dresner and Peter Stone, In AAMAS 2007 Workshop on Adaptive and Learning Agents, pp. 34-39, Honolulu, Hawaii, USA, May 2007.
Learning Synchronous Grammars for Semantic Parsing with Lambda Calculus 2007
Yuk Wah Wong and Raymond J. Mooney, In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-2007), Prague, Czech Republic, June 2007.
Learning to Extract Relations from the Web using Minimal Supervision 2007
Razvan C. Bunescu and Raymond J. Mooney, In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL'07), Prague, Czech Republic, June 2007.
Learning to predict the effects of actions: synergy between rules and landmarks 2007
Jonathan Mugan and Benjamin Kuipers, In Proceedings of the International Conference on Development and Learning (ICDL-07) 2007.
Machine Learning for On-Line Hardware Reconfiguration 2007
Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin, In The 20th International Joint Conference on Artificial Intelligence, pp. 1113-1118, January 2007.
Mapping and Revising Markov Logic Networks for Transfer Learning 2007
Lilyana Mihalkova, Tuyen N. Huynh, Raymond J. Mooney, In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI-07), pp. 608-614, Vancouver, BC, July 2007.
MARLEDA: Effective Distribution Estimation Through Markov Random Fields 2007
Matthew Alden, PhD Thesis, Department of Computer Sciences, the University of Texas at Austin. Also Technical Report AI07-349.
Model-Based Exploration in Continuous State Spaces 2007
Nicholas K. Jong and Peter Stone, In The Seventh Symposium on Abstraction, Reformulation, and Approximation, July 2007.
Model-Based Function Approximation for Reinforcement Learning 2007
Nicholas K. Jong and Peter Stone, In The Sixth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
Modeling the self-organization of color selectivity in the visual cortex 2007
Judah Ben De Paula, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Multiagent learning is not the answer. It is the question 2007
Peter Stone, Artificial Intelligence, Vol. 171 (2007), pp. 402-05.
Multiple Instance Learning for Sparse Positive Bags 2007
Razvan C. Bunescu and Raymond J. Mooney, In Proceedings of the 24th Annual International Conference on Machine Learning (ICML-2007), Corvallis, OR, June 2007.
Planning Actions to Enable Color Learning on a Mobile Robot 2007
Mohan Sridharan and Peter Stone, International Journal of Information and Systems Sciences, Vol. 3, 3 (2007), pp. 510-25.
Propositional Theories are Strongly equivalent to Logic Programs 2007
Pedro Cabalar and Paolo Ferraris, Theory and Practice of Logic Programming, Vol. 7 (2007), pp. 745-759.
Pyramid Match Hashing: Sub-Linear Time Indexing Over Partial Correspondences 2007
K. Grauman and T. Darrell, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2007.
Reinforcement Learning in High-Diameter, Continuous Environments 2007
Jefferson Provost, PhD Thesis, Computer Sciences Department, University of Texas at Austin.
Representation Transfer for Reinforcement Learning 2007
Matthew E. Taylor and Peter Stone, In AAAI 2007 Fall Symposium on Computational Approaches to Representation Change during Learning and Development, November 2007.
Robot Developmental Learning of an Object Ontology Grounded in Sensorimotor Experience 2007
Joseph Modayil, PhD Thesis, Computer Sciences Department, University of Texas at Austin.
Selective Visual Attention for Object Detection on a Legged Robot 2007
Daniel Stronger and Peter Stone, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), Vol. 4434, pp. 158-170, Berlin 2007. Springer Verlag.
Self-Organizing Distinctive State Abstraction Using Options 2007
Jefferson Provost, Benjamin J. Kuipers, and Risto Miikkulainen, In Proceedings of the 7th International Conference on Epigenetic Robotics 2007.
Semantic Boost on Episodic Associations: An Empirically Based Computational Model 2007
Yaron Silberman, Shlomo Bentin, and Risto Miikkulainen, Cognitive Science, Vol. 31 (2007), pp. 645--671.
Semi-Supervised Learning for Semantic Parsing using Support Vector Machines 2007
Rohit J. Kate and Raymond J. Mooney, In Proceedings of the Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics, Short Papers (NAACL/HLT-2007), pp. 81--84, Rochester...
Sharing the Road: Autonomous Vehicles meet Human Drivers 2007
Kurt Dresner and Peter Stone, In The 20th International Joint Conference on Artificial Intelligence, pp. 1263-68, January 2007.
Sneaking up on the Hard Problem of consciousness 2007
Benjamin Kuipers, In AI and Consciousness, AAAI Fall Symposium Series 2007.
SpAM: sparse additive models 2007
P. Ravikumar, J. Lafferty, H. Liu, and L. Wasserman, In Neural Information Processing Systems 2007.
Statistical Relational Learning for Natural Language Information Extraction 2007
Razvan Bunescu and Raymond J. Mooney, In Introduction to Statistical Relational Learning, L. Getoor and B. Taskar (Eds.), pp. 535-552, Cambridge, MA 2007. MIT Press.
Structure Based Color Learning on a Mobile Robot under Changing Illumination 2007
Mohan Sridharan and Peter Stone, Autonomous Robots, Vol. 23, 3 (2007), pp. 161-182.
System Identification for the Hodgkin-Huxley Model using Artificial Neural Networks 2007
Manish Saggar, Tekin Mericli, Sari Andoni, Risto Miikkulainen, In Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, August 2007.
Task Encoding, Motion Planning and Intelligent Control with Qualitative Models 2007
Subramanian Ramamoorthy, PhD Thesis, Electrical and Computer Engineering Department, University of Texas at Austin.
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison 2007
Matthew E. Taylor, Shimon Whiteson, and Peter Stone, In Proceedings of the Twenty-Second Conference on Artificial Intelligence, pp. 1675-1678, July 2007. Nectar Track.
The Chin Pinch: A Case Study in Skill Learning on a Legged Robot 2007
Peggy Fidelman and Peter Stone, In RoboCup-2006: Robot Soccer World Cup X, Gerhard Lakemeyer and Elizabeth Sklar and Domenico Sorenti and Tomoichi Takahashi (Eds.), Vol. 4434, pp. 59-71, Berlin 2007. Springer Verlag.
The Pyramid Match: Efficient Learning with Partial Correspondences 2007
K. Grauman, In Association for the Advancement of Artificial Intelligence (AAAI), Nectar track 2007.
The Semantics of Variables in Action Descriptions 2007
Vladimir Lifschitz and Wanwan Ren, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 1025-1030 2007.
The UT Austin Villa 3D Simulation Soccer Team 2007 2007
Shivaram Kalyanakrishnan and Peter Stone, Technical Report AI-07-348, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Transfer Learning via Inter-Task Mappings for Temporal Difference Learning 2007
Matthew E. Taylor, Peter Stone, and Yaxin Liu, Journal of Machine Learning Research, Vol. 8, 1 (2007), pp. 2125-2167.
Transfer via Inter-Task Mappings in Policy Search Reinforcement Learning 2007
Matthew E. Taylor, Shimon Whiteson, and Peter Stone, In Proceedings of the 6th International Joint Conference on Autonomous Agents and Multiagent Systems, May 2007.
Using a Mini-UAV to Support Wilderness Search and Rescue Practices for Human-Robot Teaming 2007
Michael A. Goodrich, Joseph L. Cooper, Julie A. Adams, Curtis Humphrey, Ron Zeeman and Brian G. Buss, In Proceedings of the IEEE International Conference on Safety, Security and Rescue Robotics, Rome, Italy, September 2007.
Variables in Action Descriptions: Merging C+ with ADL 2007
Vladimir Lifschitz and Wanwan Ren, In Working Notes of the 8th International Symposium on Logical Formalizations of Commonsense Reasoning (as part of the AAAI Spring Symposium Series), pp. 83--88 2007.
Where do actions come from? Autonomous robot learning of objects and actions 2007
Joseph Modayil and Benjamin Kuipers, In AAAI Spring Symposium Series 2007, Control Mechanisms for Spatial Knowledge Processing in Cognitive / Intelligent Systems 2007.
Why the Monkey Needs the Box: a Serious Look at a Toy Domain 2007
Selim T. Erdoğan, Paolo Ferraris, Vladimir Lifschitz and Wanwan Ren, In Working Notes of the 7th IJCAI International Workshop on Nonmonotonic Reasoning, Action and Change (NRAC'07), pp. 57--63 2007.
Adapting proposal distributions for accurate, efficient mobile robot localization 2006
Patrick Beeson, Aniket Murarka, and Benjamin Kuipers, In IEEE International Conference on Robotics and Automaton (ICRA-06) 2006.
A Generalization of the Lin-Zhao Theorem 2006
Paolo Ferraris, Joohyung Lee and Vladimir Lifschitz, Annals of Mathematics and Artificial Intelligence, Vol. 47 (2006), pp. 79-101.
A Knowledge Module: Buying and Selling 2006
Joohyung Lee and Vladimir Lifschitz, In Working Notes of the AAAI Symposium on Formalizing Background Knowledge 2006.
A Modular Action Description Language 2006
Vladimir Lifschitz and Wanwan Ren, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 853-859 2006.
A Multi-Robot System for Continuous Area Sweeping Tasks 2006
Mazda Ahmadi and Peter Stone, In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 1724-1729, May 2006.
A Unified Knowledge Based Approach for Sense Disambiguation and Semantic Role Labeling 2006
Peter Yeh, Bruce Porter, Ken Barker, In Proceedings of the Twenty-First National Conference on Artificial Intelligence 2006.
Actions as Special Cases 2006
Selim T. Erdoğan and Vladimir Lifschitz, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), pp. 377-387 2006.
Adapting to Workload Changes Through On-The-Fly Reconfiguration 2006
Jonathan Wildstrom, Peter Stone, Emmett Witchel, and Mike Dahlin, Technical Report UT-AI-TR-06-330, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Adaptive Blocking: Learning to Scale Up Record Linkage 2006
Mikhail Bilenko, Beena Kamath, Raymond J. Mooney, In Proceedings of the Sixth IEEE International Conference on Data Mining (ICDM-06), pp. 87--96, Hong Kong, December 2006.
Adaptive Mechanism Design: A Metalearning Approach 2006
David Pardoe, Peter Stone, Maytal Saar-Tsechansky, and Kerem Tomak, In The Eighth International Conference on Electronic Commerce, pp. 92-102, August 2006.
Answer Set Programming based on Propositional Satisfiability 2006
Enrico Giunchiglia, Yuliya Lierler, and Marco Maratea, Journal of Automated Reasoning, Vol. 36 (2006), pp. 345-377.
Automatic Heuristic Construction in a Complete General Game Player 2006
Gregory Kuhlmann, Kurt Dresner, and Peter Stone, In Proceedings of the 21st National Conference on Artificial Intelligence, pp. 1457-62, July 2006.
Autonomous Planned Color Learning on a Mobile Robot Without Labeled Data 2006
Mohan Sridharan and Peter Stone, In The Ninth International Conference on Control, Automation, Robotics and Vision, December 2006.
Autonomous Shape Model Learning for Object Localization and Recognition 2006
Joseph Modayil and Benjamin Kuipers, In IEEE International Conference on Robotics and Automaton 2006.
Building local safety maps for a wheelchair robot using vision and lasers 2006
Aniket Murarka, Joseph Modayil, and Benjamin Kuipers, In Canadian Conference on Computer and Robot Vision (CRV-06) 2006.
Causal Theories as Logic Programs 2006
Paolo Ferraris, In Proceedings of Workshop on Logic Programming 2006.
Cobot in LambdaMOO: An Adaptive Social Statistics Agent 2006
Charles Lee Isbell, Michael Kearns, Satinder Singh, Christian Shelton, Peter Stone, and Dave Kormann, Autonomous Agents and Multiagent Systems, Vol. 13, 3 (2006), pp. 36-41.
Coevolution of Neural Networks using a Layered Pareto Archive 2006
German A. Monroy, Kenneth O. Stanley, Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 329-336, Seattle, Washington, July 2006. New York, NY: ACM Press.
Comparing Evolutionary and Temporal Difference Methods for Reinforcement Learning 2006
Matthew Taylor, Shimon Whiteson, and Peter Stone, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1321-28, July 2006.
Computational Intelligence in Games 2006
Risto Miikkulainen, Bobby D. Bryant, Ryan Cornelius, Igor V. Karpov, Kenneth O. Stanley, and Chern Han Yong, In Computational Intelligence: Principles and Practice, Gary Y. Yen and David B. Fogel (Eds.), Piscataway, NJ 2006. IEEE Computational Intelligence Society.
Converting RGB Images to LMS Cone Activations 2006
Judah B. De Paula, Technical Report, Department of Computer Sciences, The University of Texas at Austin. Technical Report 06-49.
Creating Intelligent Agents in Games 2006
Risto Miikkulainen, The Bridge (2006), pp. 5-13.
Designing Safe, Profitable Automated Stock Trading Agents Using Evolutionary Algorithms 2006
Harish Subramanian, Subramanian Ramamoorthy, Peter Stone, and Benjamin Kuipers, In Proceedings of the Genetic and Evolutionary Computation Conference, July 2006.
Developing navigation behavior through self-organizing distinctive state abstraction 2006
Jefferson Provost, Benjamin J. Kuipers, and Risto Miikkulainen, Connection Science, Vol. 18 (2006), pp. 159-172.
Discriminative Reranking for Semantic Parsing 2006
Ruifang Ge and Raymond J. Mooney, In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL-06), Sydney, Australia, Jul...
Efficient Non-Linear Control through Neuroevolution 2006
Faustino Gomez, Juergen Schmidhuber, and Risto Miikkulainen, In Proceedings of the European Conference on Machine Learning, pp. 654-662, Berlin 2006. Springer.
Elementary Sets for Logic Programs 2006
Martin Gebser, Joohyung Lee, and Yuliya Lierler, In Proceedings of National Conference on Artificial Intelligence (AAAI) 2006.
Eliminating Weight Constraints in Polynomial Time 2006
Paolo Ferraris, unpublished. Unpublished draft.
Establishing an Appropriate Learning Bias Through Development 2006
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen, In Proceedings of the Fifth International Conference on Development and Learning (ICDL-2006) 2006.
Evolutionary Function Approximation for Reinforcement Learning 2006
Shimon Whiteson and Peter Stone, Journal of Machine Learning Research, Vol. 7 (2006), pp. 877-917.
Evolving a Real-World Vehicle Warning System 2006
Nate Kohl, Kenneth Stanley, Risto Miikkulainen, Michael Samples, and Rini Sherony, In Proceedings of the Genetic and Evolutionary Computation Conference 2006.
Evolving Robot Arm Controllers Using the NEAT Neuroevolution Method 2006
Thomas W. D'Silva, Masters Thesis, Department of Electrical and Computer Engineering, The University of Texas at Austin.
Evolving Stochastic Controller Networks for Intelligent Game Agents 2006
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the 2006 Congress on Evolutionary Computation, Piscataway, NJ 2006. IEEE.
Evolving Visibly Intelligent Behavior for Embedded Game Agents 2006
Bobby D. Bryant, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI-06-334.
Experiments with SAT-based Answer Set Programming 2006
Enrico Giunchiglia, Yuliya Lierler, Marco Maratea, and Armando Tacchella, In Search and Logic: Answer Set Programming and SAT, LaSh-06, A Workshop affiliated with ICLP, as part of FLoC 2006.
Exploiting Sensor Symmetries in Example-based Training for Intelligent Agents 2006
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the {IEEE} Symposium on Computational Intelligence and Games, Sushil M. Louis and Graham Kendall (Eds.), pp. 90-97, Piscataway, NJ 2006. IEEE.
Fast and Effective Worm Fingerprinting via Machine Learning 2006
Stewart Yang, Jianping Song, Harish Rajamani, Taewon Cho, Yin Zhang and Raymond Mooney, Technical Report AI-06-335, Artificial Intelligence Lab, The University of Texas at Austin. This is a longer version of our ICAC-2006 paper.
Fast and Effective Worm Fingerprinting via Machine Learning 2006
Stewart Yang, Jianping Song, Harish Rajamani, Taewon Cho, Yin Zhang and Raymond Mooney, In Proceedings of the 3rd IEEE International Conference on Autonomic Computing (ICAC-2006), Dublin, Ireland, June 2006. Poster Session.
From Pixels to Multi-Robot Decision-Making: A Study in Uncertainty 2006
Peter Stone, Mohan Sridharan, Daniel Stronger, Gregory Kuhlmann, Nate Kohl, Peggy Fidelman, and Nicholas K. Jong, Robotics and Autonomous Systems, Vol. 54, 11 (2006), pp. 933-43. Special issue on Planning Under Uncertainty in Robotics..
Grounding Language in Descriptions of Scenes 2006
Paul Williams and Risto Miikkulainen, In Proceedings of the 28th Annual Meeting of the Cognitive Science Society 2006.
High-dimensional graphical model selection using l1-regularized logistic regression 2006
M. J. Wainwright, P. Ravikumar, and J. Lafferty, In Neural Information Processing Systems 2006.
Human-Usable and Emergency Vehicle-Aware Control Policies for Autonomous Intersection Management 2006
Kurt Dresner and Peter Stone, In AAMAS 2006 Workshop on Agents in Traffic and Transportation, May 2006.
Incorporating Advice into Neuroevolution of Adaptive Agents 2006
Chern Han Yong, Kenneth O. Stanley, Risto Miikkulainen, and Igor V. Karpov, In Proceedings of the Second Artificial Intelligence and Interactive Digital Entertainment Conference, pp. 98-104, Menlo Park, CA 2006. AAAI Press.
Integrating Co-occurrence Statistics with Information Extraction for Robust Retrieval of Protein Interactions from Medline 2006
Razvan Bunescu, Raymond Mooney, Arun Ramani and Edward Marcotte, In Proceedings of the HLT-NAACL Workshop on Linking Natural Language Processing and Biology (BioNLP'06), pp. 49-56, New York, NY, June 2006.
Integration and Evaluation of Exploration-Based Learning in Games 2006
Igor V. Karpov, Thomas D'Silva, Craig Varrichio, Kenneth O. Stanley, Risto Miikkulainen, In Proceedings of the {IEEE} Symposium on Computational Intelligence and Games, Reno, NV 2006. IEEE.
Joint Maps for Orientation, Eye, and Direction Preference in a Self-Organizing Model of V1 2006
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1272--1276.
Keepaway Soccer: From Machine Learning Testbed to Benchmark 2006
Peter Stone, Gregory Kuhlmann, Matthew E. Taylor, and Yaxin Liu, In RoboCup-2005: Robot Soccer World Cup IX, Itsuki Noda and Adam Jacoff and Ansgar Bredenfeld and Yasutake Takahashi (Eds.), Vol. 4020, pp. 93-105, Berlin 2006. Springer Verlag.
Keeping in Touch: Maintaining Biconnected Structure by Homogeneous Robots 2006
Mazda Ahmadi and Peter Stone, In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 580-85, July 2006.
Know Thine Enemy: A Champion RoboCup Coach Agent 2006
Gregory Kuhlmann, William B. Knox, and Peter Stone, In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1463-68, July 2006.
Learnable Similarity Functions and Their Application to Record Linkage and Clustering 2006
Mikhail Bilenko, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 136 pages.
Learning for Semantic Parsing with Statistical Machine Translation 2006
Yuk Wah Wong and Raymond J. Mooney, In Proceedings of Human Language Technology Conference / North American Chapter of the Association for Computational Linguistics Annual Meeting (HLT-NAACL-06), pp. 439-446, New York City, NY 20...
Learning Language from Perceptual Context: A Challenge Problem for AI 2006
Raymond J. Mooney, In Proceedings of the 2006 AAAI Fellows Symposium, Boston, MA, July 2006.
Learning Semantic Parsers Using Statistical Syntactic Parsing Techniques 2006
Ruifang Ge, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin" , year="2006.
Low-Discrepancy Curves and Efficient Coverage of Space 2006
Subramanian Ramamoorthy, Ram Rajagopal, Qing Ruan, Lothar Wenzel, In Algorithmic Foundations of Robotics VII 2006. Springer-Verlag.
Model Generation for Generalized Quantifiers via Answer Set Programming 2006
Yuliya Lierler and Guenther Goerz, In 8th Conference on Natural Language Processing (KONVENS) 2006.
Multiagent Traffic Management: Opportunities for Multiagent Learning 2006
Kurt Dresner and Peter Stone, In LAMAS 2005, K. Tuyls et al. (Eds.), Vol. 3898, pp. 129-138, Berlin 2006. Springer Verlag.
On-Line Evolutionary Computation for Reinforcement Learning in Stochastic Domains 2006
Shimon Whiteson and Peter Stone, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 1577-84, July 2006.
Parametrization and computations in shape spaces with area and boundary invariants 2006
Subramanian Ramamoorthy, Benjamin J. Kuipers and Lothar Wenzel, In Proc. Fall Workshop on Computational and Combinatorial Geometry, Northampton, MA 2006.
Preconditioner approximations for probabilistic graphical models 2006
P. Ravikumar and J. Lafferty, In Neural Information Processing Systems, pp. 1113-1120 2006.
Predictive Planning for Supply Chain Management 2006
David Pardoe and Peter Stone, In Proceedings of the International Conference on Automated Planning and Scheduling, June 2006.
Prenatal Development of Ocular Dominance and Orientation Maps in a Self-Organizing Model of V1 2006
Stefanie Jegelka, James A. Bednar, and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1291--1296.
PRISM: Precision-aware Aggregation for Scalable Monitoring 2006
Navendu Jain, Dmitry Kit, Prince Mahajan, Praveen Yalagandula, Mike Dahlin, and Yin Zhang, Technical Report, University of Texas at Austin.
Probabilistic Semi-Supervised Clustering with Constraints 2006
Sugato Basu, Mikhail Bilenko, Arindam Banerjee and Raymond J. Mooney, In Semi-Supervised Learning, O. Chapelle and B. Sch{"{o}}lkopf and A. Zien (Eds.), Cambridge, MA 2006. MIT Press.
Quadratic programming relaxations for metric labeling and Markov random field MAP estimation 2006
P. Ravikumar and J. Lafferty, In International Conference on Machine learning (ICML), pp. 737-744 2006.
Qualitative hybrid control of dynamic bipedal walking 2006
Subramanian Ramamoorthy, Benjamin Kuipers, In Robotics: Science and Systems II, G. S. Sukhatme, S. Schaal, W. Burgard and D. Fox (Eds.) 2006. MIT Press.
Real-Time Evolution of Neural Networks in the NERO Video Game 2006
Kenneth O. Stanley, Bobby D. Bryant, Igor Karpov, Risto Miikkulainen, In Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI-2006), pp. 1671--1674, Boston, MA 2006. Meno Park, CA: AAAI Press.
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning 2006
Shimon Whiteson and Peter Stone, In {AAAI} 2006: {P}roceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 518-523, July 2006.
Selecting for Evolvable Representations 2006
Joseph Reisinger and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2006.
Self-Organization of Hierarchical Visual Maps with Feedback Connections 2006
Yiu Fai Sit and Risto Miikkulainen, Neurocomputing, Vol. 69 (2006), pp. 1309-1312.
Subsequence Kernels for Relation Extraction 2006
Razvan Bunescu and Raymond J. Mooney, In Advances in Neural Information Processing Systems, Vol. 18: Proceedings of the 2005 Conference (NIPS), Y. Weiss, B. Schoelkopf, J. Platt (Eds.) 2006.
TacTex-2005: A Champion Supply Chain Management Agent 2006
David Pardoe and Peter Stone, In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 1489-94, July 2006.
Temporal Phylogenetic Networks and Logic Programming 2006
Esra Erdem, Vladimir Lifschitz and Don Ringe, Theory and Practice of Logic Programming, Vol. 6 (2006), pp. 539-558.
The Effect of Delivery Method on Conceptual and Strategy Development 2006
Lisa C. Kaczmarczyk, Mary Z. Last, Risto Miikkulainen, In Proceedings of the 28th Annual Conference of the Cognitive Science Society 2006.
The UT Austin Villa 2006 RoboCup Four-Legged Team 2006
Peter Stone, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Tekin Mericli, Mohan Sridharan, and Shao-en Yu, Technical Report UT-AI-TR-06-337, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Towards Autonomous Sensor and Actuator Model Induction on a Mobile Robot 2006
Daniel Stronger and Peter Stone, Connection Science, Vol. 18, 2 (2006), pp. 97-119. Special Issue on Developmental Robotics..
Transfer Learning with Markov Logic Networks 2006
Lilyana Mihalkova and Raymond Mooney, In Proceedings of the ICML-06 Workshop on Structural Knowledge Transfer for Machine Learning, Pittsburgh, PA, June 2006.
Unsupervised Learning of Categories from Sets of Partially Matching Image Features 2006
K. Grauman and T. Darrell, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2006.
Using Active Relocation to Aid Reinforcement Learning 2006
Lilyana Mihalkova and Raymond Mooney, In Prodeedings of the 19th International FLAIRS Conference (FLAIRS-2006), pp. 580-585, Melbourne Beach, FL, May 2006.
Using Encyclopedic Knowledge for Named Entity Disambiguation 2006
Razvan Bunescu and Marius Pasca, In Proceesings of the 11th Conference of the European Chapter of the Association for Computational Linguistics (EACL-06), pp. 9-16, Trento, Italy 2006.
Using String-Kernels for Learning Semantic Parsers 2006
Rohit J. Kate and Raymond J. Mooney, In ACL 2006: Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the ACL, pp. 913-920, Morristown, NJ, USA 2006. Association for Computa...
Value Function Transfer for General Game Playing 2006
Bikramjit Banerjee, Gregory Kuhlmann, and Peter Stone, In ICML workshop on Structural Knowledge Transfer for Machine Learning, June 2006.
Value-Function-Based Transfer for Reinforcement Learning Using Structure Mapping 2006
Yaxin Liu and Peter Stone, In Proceedings of the Twenty-First National Conference on Artificial Intelligence, pp. 415-20, July 2006.
Why Are There So Many Loop Formulas? 2006
Vladimir Lifschitz and Alexander Razborov, ACM Transactions on Computational Logic, Vol. 7 (2006), pp. 261-268.
A Kernel-based Approach to Learning Semantic Parsers 2005
Rohit J. Kate, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin.
A Model-Based Approach to Robot Joint Control 2005
Daniel Stronger and Peter Stone, In RoboCup-2004: Robot Soccer World Cup VIII, Daniele Nardi and Martin Riedmiller and Claude Sammut (Eds.), Vol. 3276, pp. 297-309, Berlin 2005. Springer Verlag.
A Model-Theoretic Counterpart of Loop Formulas 2005
Joohyung Lee, In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 503-508 2005. Professional Book Center.
A Picture is Worth a Thousand Keywords: Image-Based Object Search on a Mobile Platform 2005
T. Yeh, K. Grauman, K. Tollmar, and T. Darrell, In Conference on Human Factors in Computing Systems (CHI) 2005.
A Polynomial-time Nash Equilibrium Algorithm for Repeated Games 2005
Michael L. Littman and Peter Stone, Decision Support Systems, Vol. 39 (2005), pp. 55-66.
A Shortest Path Dependency Kernel for Relation Extraction 2005
R. C. Bunescu, and Raymond J. Mooney, In Proceedings of the Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing (HLT/EMNLP-05), pp. 724-731, Vancouver, BC, October 2005.
A Statistical Semantic Parser that Integrates Syntax and Semantics 2005
Ruifang Ge and Raymond J. Mooney, In Proceedings of CoNLL-2005, Ann Arbor, Michigan, June 2005.
A Subsymbolic Model of Complex Story Understanding 2005
Peggy Fidelman, Risto Miikkulainen and Ralph Hoffman, In Proceedings of the 27th Annual Meeting of the Cognitive Science Society 2005.
Academic AI and Video Games: A Case Study of Incorporating Innovative Academic Research into a Video Game Prototype 2005
Aliza Gold, In Proceedings of the IEEE 2005 Symposium on Computational Intelligence and Games (CIG'05) 2005. Piscataway, NJ: IEEE.
Active Learning for Probability Estimation using Jensen-Shannon Divergence 2005
P. Melville, S. M. Yang, M. Saar-Tsechansky and Raymond J. Mooney, In Proceedings of the 16th European Conference on Machine Learning, pp. 268--279, Porto, Portugal, October 2005.
Adaptive Product Normalization: Using Online Learning for Record Linkage in Comparison Shopping 2005
Mikhail Bilenko, Sugato Basu, and Mehran Sahami, In Proceedings of the 5th International Conference on Data Mining (ICDM-2005), pp. 58--65, Houston, TX, November 2005.
Alignments and String Similarity in Information Integration: A Random Field Approach 2005
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the 2005 Dagstuhl Seminar on Machine Learning for the Semantic Web, Dagstuhl, Germany, February 2005.
An Expected Utility Approach to Active Feature-value Acquisition 2005
P. Melville, M. Saar-Tsechansky, F. Provost and Raymond J. Mooney, In Proceedings of the International Conference on Data Mining, pp. 745-748, Houston, TX, November 2005.
Answer Sets for Propositional Theories 2005
Paolo Ferraris, In Proceedings of International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), pp. 119-131 2005.
Associating Unseen Events: Semantically Mediated Formation of Episodic Associations 2005
Yaron Silberman, Risto Miikkulainen, and Shlomo Bentin, Psychological Science, Vol. 16 (2005), pp. 161-166.
Automated Reasoning about Actions 2005
Joohyung Lee, PhD Thesis, University of Texas at Austin.
Automatic Feature Selection via Neuroevolution 2005
Shimon Whiteson, Peter Stone, Kenneth O. Stanley, Risto Miikkulainen, and Nate Kohl, In Proceedings of the Genetic and Evolutionary Computation Conference, June 2005.
Autonomous Color Learning on a Mobile Robot 2005
Mohan Sridharan and Peter Stone, In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
Avoiding the ``Streetlight Effect'': Tracking by Exploring Likelihood Modes 2005
D. Demirdjian, L. Taycher, G. Shakhnarovich, K. Grauman, and T. Darrell, In IEEE International Conference on Computer Vision (ICCV) 2005.
Bayesian Models of Nonstationary Markov Decision Problems 2005
Nicholas K. Jong and Peter Stone, In IJCAI 2005 workshop on Planning and Learning in A Priori Unknown or Dynamic Domains, August 2005.
Behavior Transfer for Value-Function-Based Reinforcement Learning 2005
Matthew E. Taylor and Peter Stone, In The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Frank Dignum and Virginia Dignum and Sven Koenig and Sarit Kraus and Munindar P. Singh and Michael Woo...
Bidding for Customer Orders in TAC SCM 2005
David Pardoe and Peter Stone, In Agent Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems (AMEC 2004), P. Faratin and J.A. Rodriguez-Aguilar (Eds.), Vol. 3435, pp. 143-157, ...
Bootstrap Learning of Foundational Representations. 2005
Benjamin Kuipers, Patrick Beeson, Joseph Modayil and Jefferson Provost, In Developmental Robotics, AAAI Spring Symposium Series 2005.
Broad-Coverage Parsing with Neural Networks 2005
Marshall R. Mayberry III and Risto Miikkulainen, Neural Processing Letters, Vol. 21 (2005), pp. 121--143.
Cmodels -- SAT-based Disjunctive Answer Set Solver 2005
Yuliya Lierler, In 8th International Conference on Logic Programming and Nonmonotonic Reasoning 2005.
Cmodels for Tight Disjunctive Logic programs 2005
Yuliya Lierler, In 19th Workshop on (Constraint) Logic Programming W(C)LP 2005, 2005-01 2005. http://www.informatik.uni-ulm.de/epin/pw/11541.
Coevolution of Neural Networks Using a Layered Pareto Archive 2005
German A. Monroy, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin.
Combining Bias and Variance Reduction Techniques for Regression 2005
Yuk Lai Suen, Prem Melville and Raymond J. Mooney, Technical Report UT-AI-TR-05-321, University of Texas at Austin. www.cs.utexas.edu/~ml/publication.
Combining Bias and Variance Reduction Techniques for Regression 2005
Y. L. Suen, P. Melville and Raymond J. Mooney, In Proceedings of the 16th European Conference on Machine Learning, pp. 741-749, Porto, Portugal, October 2005.
Comments: The Sensitivity of Economic Statistics to Coding Errors in Personal Identifiers 2005
W. W. Cohen, S. Fienberg, and P. Ravikumar, Journal of Business and Economic Statistics, Vol. 23, 2 (2005), pp. 160-162.
Comparative Experiments on Learning Information Extractors for Proteins and their Interactions 2005
Razvan Bunescu, Ruifang Ge, Rohit J. Kate, Edward M. Marcotte, Raymond J. Mooney, Arun Kumar Ramani, and Yuk Wah Wong, Artificial Intelligence in Medicine (special issue on Summarization and Information Extraction from Medical Documents), 2 (2005), pp. 139-155.
Consciousness: Drinking from the Firehose of Experience 2005
Benjamin Kuipers, In National Conference on Artificial Intelligence (AAAI-05) 2005.
Consolidating the Set of Known Human Protein-Protein Interactions in Preparation for Large-Scale Mapping of the Human Interactome 2005
A.K. Ramani, R.C. Bunescu, Raymond J. Mooney and E.M. Marcotte, Genome Biology, Vol. 6, 5 (2005), pp. r40.
Constructing Good Learners Using Evolved Pattern Generators 2005
Vinod K. Valsalam, James A. Bednar, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO-2005, H.-G. Beyer and others (Eds.), pp. 11-18 2005.
Constructing Visual Function Through Prenatal and Postnatal Learning 2005
James A. Bednar and Risto Miikkulainen, In Neuroconstructivism, Vol. 2: Perspectives and Prospects, Denis Mareschal and Mark H. Johnson and Sylvain Sirois and Michael Spratling and Michael S. C. Thomas and Gert Westermann (Eds.), pp....
Continuous Area Sweeping: A Task Definition and Initial Approach 2005
Mazda Ahmadi and Peter Stone, In The 12th International Conference on Advanced Robotics, July 2005.
Creating Diverse Ensemble Classifiers to Reduce Supervision 2005
Prem Melville, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 141 pages. Technical Report TR-05-49.
Developing Adaptive Auction Mechanisms 2005
David Pardoe and Peter Stone, SIGecom Exchanges, Vol. 5, 3 (2005), pp. 1-10.
Disjunctive Answer Set Programming via Satisfiability 2005
Yuliya Lierler, In 3rd Intl. Workshop on Answer Set Programming: Advances in Theory and Implementation 2005.
Economical Active Feature-value Acquisition through Expected Utility Estimation 2005
P. Melville, M. Saar-Tsechansky, F. Provost and Raymond J. Mooney, In Proceedings of the KDD-05 Workshop on Utility-Based Data Mining, pp. 10-16, Chicago, IL, August 2005.
Effective Image Compression Using Evolved Wavelets 2005
Uli Grasemann and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
Efficient Credit Assignment through Evaluation Function Decomposition 2005
Adrian Agogino, Kagan Tumer, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, 2005.
Efficient Image Matching with Distributions of Local Invariant Features 2005
K. Grauman and T. Darrell, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2005.
Evolving Keepaway Soccer Players through Task Decomposition 2005
Shimon Whiteson, Nate Kohl, Risto Miikkulainen, and Peter Stone, Machine Learning, Vol. 59, 1 (2005), pp. 5-30.
Evolving Neural Network Agents in the NERO Video Game 2005
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen, In Proceedings of the IEEE 2005 Symposium on Computational Intelligence and Games (CIG'05), Piscataway, NJ 2005. IEEE.
Evolving Neural Network Ensembles for Control Problems 2005
David Pardoe, Michael Ryoo, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
Explaining Recommendations: Satisfaction vs. Promotion 2005
Mustafa Bilgic and Raymond J. Mooney, In Proceedings of Beyond Personalization 2005: A Workshop on the Next Stage of Recommender Systems Research at the 2005 International Conference on Intelligent User Interfaces, San Diego, CA, J...
Function Approximation via Tile Coding: Automating Parameter Choice 2005
Alexander A. Sherstov and Peter Stone, In SARA 2005, J.-D. Zucker and I. Saitta (Eds.), Vol. 3607, pp. 194-205, Berlin 2005. Springer Verlag.
Improving Action Selection in MDP's via Knowledge Transfer 2005
Alexander A. Sherstov and Peter Stone, In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
Improving Prescripted Agent Behavior with Neuroevolution 2005
Ryan Cornelius, Technical Report HR-05-01, Department of Computer Sciences, The University of Texas at Austin.
Incorporating Advice into Evolution of Neural Networks 2005
Chern Han Yong, Kenneth O. Stanley, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2005) 2005. Late Breaking Papers.
Indirect Anaphora Resolution as Semantic Path Search 2005
James Fan, Ken Barker, Bruce Porter, In Proceedings of Third International Conference on Knowledge Capture 2005.
Learning Basic Navigation for Personal Satellite Assistant Using Neuroevolution 2005
Yiu Fai Sit and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
Learning for Collective Information Extraction 2005
Razvan C. Bunescu, Technical Report TR-05-02, Department of Computer Sciences, University of Texas at Austin. Ph.D. proposal.
Learning for Semantic Parsing Using Statistical Machine Translation Techniques 2005
Yuk Wah Wong, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin.
Learning to Transform Natural to Formal Languages 2005
Rohit J. Kate, Yuk Wah Wong and Raymond J. Mooney, In Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI-05), pp. 1062-1068, Pittsburgh, PA, July 2005.
Learning Visual Scene Descriptions: An Approach to Symbol Grounding 2005
Paul Williams, Technical Report TR-06-01, Department of Computer Science, The University of Texas at Austin.
Matching Utterances to Rich Knowledge Structures to Acquire a Model of the Speaker's Goal 2005
Peter Yeh, Bruce Porter, Ken Barker, In Proceedings of Third International Conference on Knowledge Capture 2005.
Mathematical Foundations of Answer Set Programming 2005
Paolo Ferraris and Vladimir Lifschitz, In We Will Show Them! Essays in Honour of Dov Gabbay, pp. 615-664 2005. King's College Publications.
Mining Knowledge from Text Using Information Extraction 2005
Raymond J. Mooney and R. Bunescu, SIGKDD Explorations (special issue on Text Mining and Natural Language Processing), Vol. 7, 1 (2005), pp. 3-10.
Model-based Overlapping Clustering 2005
A. Banerjee, C. Krumpelman, S. Basu, Raymond J. Mooney and Joydeep Ghosh, In Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-05) 2005.
Multiagent Traffic Management: An Improved Intersection Control Mechanism 2005
Kurt Dresner and Peter Stone, In The Fourth International Joint Conference on Autonomous Agents and Multiagent Systems, Frank Dignum and Virginia Dignum and Sven Koenig and Sarit Kraus and Munindar P. Singh and Michael Woo...
Neuroevolution of an Automobile Crash Warning System 2005
Kenneth Stanley, Nate Kohl, Rini Sherony, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2005.
On Modular Translations and Strong Equivalence 2005
Paolo Ferraris, In Proceedings of International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), pp. 79-91 2005.
Practical Vision-Based Monte Carlo Localization on a Legged Robot 2005
Mohan Sridharan, Gregory Kuhlmann, and Peter Stone, In IEEE International Conference on Robotics and Automation, April 2005.
Real-Time Learning in the NERO Video Game 2005
Kenneth O. Stanley, Ryan Cornelius, Risto Miikkulainen, Thomas D'Silva, and Aliza Gold, In Proceedings of the Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE 2005) Demo Papers 2005.
Real-time Neuroevolution in the NERO Video Game 2005
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen, IEEE Transactions on Evolutionary Computation (2005), pp. 653-668. IEEE.
Real-Time Vision on a Mobile Robot Platform 2005
Mohan Sridharan and Peter Stone, In IEEE/RSJ International Conference on Intelligent Robots and Systems, August 2005.
Reinforcement Learning for RoboCup-Soccer Keepaway 2005
Peter Stone, Richard S. Sutton, and Gregory Kuhlmann, Adaptive Behavior, Vol. 13, 3 (2005), pp. 165-188.
Retaining Learned Behavior During Real-Time Neuroevolution 2005
Thomas D'Silva, Roy Janik, Michael Chrien, Kenneth O. Stanley and Risto Miikkulainen, Artificial Intelligence and Interactive Digital Entertainment (2005). American Association for Artificial Intelligence.
Self-organization of color opponent receptive fields and laterally connected orientation maps 2005
James A. Bednar, Judah B. De Paula, and Risto Miikkulainen, Neurocomputing, Vol. 65--66 (2005), pp. 69-76.
Semi-supervised Clustering: Probabilistic Models, Algorithms and Experiments 2005
Sugato Basu, PhD Thesis, University of Texas at Austin.
Semi-supervised Graph Clustering: A Kernel Approach 2005
B. Kulis, S. Basu, I. Dhillon and Raymond J. Mooney, In Proceedings of the 22nd International Conference on Machine Learning, pp. 457--464, Bonn, Germany, August 2005. (Distinguished Student Paper Award).
State Abstraction Discovery from Irrelevant State Variables 2005
Nicholas K. Jong and Peter Stone, In Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, pp. 752-757, August 2005.
The Acquisition of Intellectual Expertise: A Computational and Empirical Theory 2005
Elizabeth C. Kaczmarczyk, PhD Thesis, Department of Computer Sciences, University of Texas at Austin.
The First International Trading Agent Competition: Autonomous Bidding Agents 2005
Peter Stone and Amy Greenwald, Electronic Commerce Research, Vol. 5, 2 (2005), pp. 229-65.
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features 2005
K. Grauman and T. Darrell, In IEEE International Conference on Computer Vision (ICCV) 2005.
The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach 2005
Gregory Kuhlmann, Peter Stone, and Justin Lallinger, In RoboCup-2004: Robot Soccer World Cup VIII, Daniele Nardi and Martin Riedmiller and Claude Sammut (Eds.), Vol. 3276, pp. 636-644, Berlin 2005. Springer Verlag.
The UT Austin Villa 2005 RoboCup Four-Legged Team 2005
Peter Stone, Kurt Dresner, Peggy Fidelman, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger, Technical Report UT-AI-TR-05-325, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Three Automated Stock-Trading Agents: A Comparative Study 2005
Alexander Sherstov and Peter Stone, In Agent Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems (AMEC 2004), P. Faratin and J.A. Rodriguez-Aguilar (Eds.), Vol. 3435, pp. 173-187, ...
Towards an Empirical Measure of Evolvability 2005
Joseph Reisinger, Kenneth O. Stanley, Risto Miikkulainen, In Genetic and Evolutionary Computation Conference {(GECCO2005)} Workshop Program, pp. 257-264, Washington, D.C. 2005. ACM Press.
Towards autonomous topological place detection using the Extended Voronoi Graph 2005
Patrick Beeson, Nicholas K. Jong, and Benjamin Kuipers, In IEEE International Conference on Robotics and Automation (ICRA-05) 2005.
Towards Illumination Invariance in the Legged League 2005
Mohan Sridharan and Peter Stone, In RoboCup-2004: Robot Soccer World Cup VIII, Daniele Nardi and Martin Riedmiller and Claude Sammut (Eds.), Vol. 3276, pp. 196-208, Berlin 2005. Springer Verlag.
Towards Self-Configuring Hardware for Distributed Computer Systems 2005
Jonathan Wildstrom, Peter Stone, E. Witchel, Raymond Mooney and M. Dahlin, In The Second International Conference on Autonomic Computing, pp. 241-249, June 2005.
Using Biomedical Literature Mining to Consolidate the Set of Known Human Protein-Protein Interactions 2005
A. Ramani, E. Marcotte, R. Bunescu and Raymond J. Mooney, In Proceedings of the ISMB/ACL-05 Workshop of the BioLINK SIG: Linking Literature, Information and Knowledge for Biology, Detroit, MI, June 2005.
Value Functions for RL-Based Behavior Transfer: A Comparative Study 2005
Matthew E. Taylor, Peter Stone, and Yaxin Liu, In Proceedings of the Twentieth National Conference on Artificial Intelligence, July 2005.
Weight Constraints as Nested Expressions 2005
Paolo Ferraris and Vladimir Lifschitz, Theory and Practice of Logic Programming, Vol. 5 (2005), pp. 45-74.
Self-Organizing Perceptual and Temporal Abstraction for Robot Reinforcement Learning 2004
Jefferson Provost, Benjamin J. Kuipers and Risto Miikkulainen, In AAAI-04 Workshop on Learning and Planning in Markov Processes 2004.
A Comparison of Inference Techniques for Semi-supervised Clustering with Hidden Markov Random Fields 2004
Mikhail Bilenko and Sugato Basu, In Proceedings of the ICML-2004 Workshop on Statistical Relational Learning and its Connections to Other Fields (SRL-2004), Banff, Canada, July 2004.
A Hierarchical Graphical Model for Record Linkage 2004
P. Ravikumar and W. W. Cohen, In Uncertainty in Artificial Intelligence (UAI), pp. 454-461 2004.
A Neurocontrol Paradigm for Intelligent Process Control using Evolutionary Reinforcement Learning 2004
Alex van Eck Conradie, PhD Thesis, Department of Chemical Engineering, University of Stellenbosch.
A Probabilistic Framework for Semi-Supervised Clustering 2004
Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney, In Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004), pp. 59-68, Seattle, WA, August 2004.
A Question-Answering System for AP Chemistry: Assessing KR&R Technologies 2004
Ken Barker, Vinay K. Chaudhri, Shaw Yi Chaw, Peter E. Clark, James Fan, David Israel, Sunil Mishra, Bruce Porter, Pedro Romero, Dan Tecuci, Peter Yeh, In The Ninth International Conference on the Principles of Knowledge Representation and Reasoning (KR2004) 2004.
A Secure Protocol for Computing String Distance Metrics 2004
P. Ravikumar, W. W. Cohen, and S. E. Fienberg, In In IEEE International Conference on Data Mining (ICDM) 04, Workshop on Privacy and Security Aspects of Data Mining 2004.
Active Feature-Value Acquisition for Classifier Induction 2004
Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney, Technical Report UT-AI-TR-04-311, Artificial Intelligence Lab, University of Texas at Austin.
Active Feature-Value Acquisition for Classifier Induction 2004
Prem Melville, Maytal Saar-Tsechansky, Foster Provost, and Raymond J. Mooney, In Proceedings of the Fourth IEEE International Conference on Data Mining (ICDM-2004), pp. 483-486, Brighton, UK, November 2004.
Active Semi-Supervision for Pairwise Constrained Clustering 2004
Sugato Basu, Arindam Banerjee, and Raymond J. Mooney, In Proceedings of the 2004 SIAM International Conference on Data Mining (SDM-04), April 2004.
Adaptive Job Routing and Scheduling 2004
Shimon Whiteson and Peter Stone, Engineering Applications of Artificial Intelligence, Vol. 17(7), 7 (2004), pp. 855-869. Corrected version.
Almost Definite Causal Theories 2004
Semra Dogandag, Paolo Ferraris, Vladimir Lifschitz, In Proc. LPNMR-7, pp. 74--86 2004.
Automatic Compilation of Protocol Insecurity Problems into Logic Programming 2004
Alesandro Armando, Luca Compagna, and Yuliya Lierler, In Proceedings of 9th {E}uropean Conference in Logics in Artificial Intelligence (JELIA-04), pp. 617-627 2004. Springer.
Bootstrap learning for object discovery 2004
Joseph Modayil and Benjamin Kuipers, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-04) 2004.
Characteristics of Forming Episodic Associations Between Words 2004
Yaron Silberman, PhD Thesis, The Hebrew University of Jerusalem.
Cmodels-2: SAT-based Answer Set Solver Enhanced to Non-tight Programs 2004
Yuliya Lierler and Marco Maratea, In Procedings of International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), pp. 346-350 2004.
Collective Information Extraction with Relational Markov Networks 2004
Razvan Bunescu and Raymond J. Mooney, In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04), pp. 439-446, Barcelona, Spain, July 2004.
Competitive Coevolution through Evolutionary Complexification 2004
Kenneth O. Stanley and Risto Miikkulainen, Journal of Artificial Intelligence Research, Vol. 21 (2004), pp. 63-100.
Contour grouping: closure effects are explained by good continuation and proximity 2004
Tal Tversky, Wilson S. Geisler and Jeffrey S. Perry, Vision Research, Vol. 44, 24 (2004), pp. 2769--2777.
Contour Integration and Segmentation with Self-Organized Lateral Connections 2004
Yoonsuck Choe and Risto Miikkulainen, Biological Cybernetics 90:75-88
Controller synthesis using qualitative models and constraints 2004
Subramanian Ramamoorthy, Benjamin Kuipers, In Proceedings of the 18th International Workshop on Qualitative Reasoning, J. de Kleer and K. Forbus (Eds.), pp. 41--50 2004.
Creating Diversity in Ensembles Using Artificial Data 2004
Prem Melville and Raymond J. Mooney, Journal of Information Fusion: Special Issue on Diversity in Multi Classifier Systems, Vol. 6, 1 (2004), pp. 99-111.
Definitions in Answer Set Programming 2004
Selim T. Erdoğan and Vladimir Lifschitz, In Proceedings of International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), Vladimir Lifschitz and Ilkka Niemel{"a} (Eds.), pp. 114-126 2004.
Diverse Ensembles for Active Learning 2004
Prem Melville and Raymond J. Mooney, In Proceedings of 21st International Conference on Machine Learning (ICML-2004), pp. 584-591, Banff, Canada, July 2004.
Efficient Allele Fitness Assignment with Self-organizing Multi-agent System 2004
Adrian Agogino and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004) Workshop Program, New York, NY 2004. Springer-Verlag.
Efficient Evolution of Neural Networks Through Complexification 2004
Kenneth O. Stanley, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Evolving a Roving Eye for Go 2004
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2004), Berlin 2004. Springer Verlag.
Evolving Reusable Neural Modules 2004
Joseph Reisinger, Kenneth O. Stanley, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference 2004.
Evolving Wavelets using a Coevolutionary Genetic Algorithm and Lifting 2004
Uli Grasemann and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 969-980, San Francisco 2004. Kaufmann.
Experiments on Ensembles with Missing and Noisy Data 2004
Prem Melville, Nishit Shah, Lilyana Mihalkova, and Raymond J. Mooney, In {Lecture Notes in Computer Science:} Proceedings of the Fifth International Workshop on Multi Classifier Systems (MCS-2004), F. Roli, J. Kittler, and T. Windeatt (Eds.), Vol. 3077, pp. 293-3...
Explanation for Recommender Systems: Satisfaction vs. Promotion 2004
Mustafa Bilgic, unpublished. Undergraduate Honor Thesis, Department of Computer Sciences, University of Texas at Austin.
Exploiting Morphological Conventions for Genetic Reuse 2004
Kenneth O. Stanley, Joseph Reisinger, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference ({GECCO}-2004) Workshop Program, Berlin 2004. Springer Verlag.
Fast Contour Matching Using Approximate Earth Mover's Distance 2004
K. Grauman and T. Darrell, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2004.
Goal-Converging Behavior Networks and Self-Solving Planning Domains 2004
Bernhard Nebel and Yuliya Lierler, In 16th European Conference on Artificial Intelligence 2004.
Guiding a Reinforcement Learner with Natural Language Advice: Initial Results in RoboCup Soccer 2004
Gregory Kuhlmann, Peter Stone, Raymond J. Mooney, and Jude W. Shavlik, In The AAAI-2004 Workshop on Supervisory Control of Learning and Adaptive Systems, July 2004.
Integrating Constraints and Metric Learning in Semi-Supervised Clustering 2004
Mikhail Bilenko, Sugato Basu, and Raymond J. Mooney, In Proceedings of 21st International Conference on Machine Learning (ICML-2004), pp. 81-88, Banff, Canada, July 2004.
Interpreting Loosely Encoded Questions 2004
James Fan, Bruce Porter, In Proceedings of the Nineteenth National Conference on Artificial Intelligence 2004.
Irrelevant Actions in Plan Generation (extended abstract) 2004
Vladimir Lifschitz and Wanwan Ren, In IX Ibero-American Workshops on Artificial Intelligence, pp. 71-78 2004.
Learnable Similarity Functions and Their Applications to Clustering and Record Linkage 2004
Mikhail Bilenko, In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, pp. 981--982, San Jose, CA, July 2004.
Learning Ball Acquisition on a Physical Robot 2004
Peggy Fidelman and Peter Stone, In International Symposium on Robotics and Automation (ISRA) 2004.
Learning Semantic Parsers: An Important But Under-Studied Problem 2004
Raymond J. Mooney, In Papers from the AAAI 2004 Spring Symposium on Language Learning: An Interdisciplinary Perspective, pp. 39--44, Stanford, CA, March 2004.
Learning Transformation Rules for Semantic Parsing 2004
Rohit J. Kate, Yuk Wah Wong, Ruifang Ge, and Raymond J. Mooney, unpublished. Unpublished Technical Report.
Local metrical and global topological maps in the Hybrid Spatial Semantic Hierarchy 2004
Benjamin Kuipers, Joseph Modayil, Patrick Beeson, Matt MacMahon, and Francesco Savelli, In IEEE International Conference on Robotics and Automation (ICRA-04) 2004.
Loop Formulas for Circumscription 2004
Joohyung Lee and Fangzhen Lin, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 281-286 2004.
Loop-closing and planarity in topological map-building 2004
Francesco Savelli and Benjamin Kuipers, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-04), pp. 1511--1517 2004.
Machine Learning for Fast Quadrupedal Locomotion 2004
Nate Kohl and Peter Stone, In Nineteenth National Conference on Artificial Intelligence, pp. 611-616, July 2004.
Mining Transformation Rules for Semantic Matching 2004
Peter Yeh, Bruce Porter, Ken Barker, In Proceedings of ECML/PKDD 2nd International Workshop on Mining Graphs, Trees and Sequences (MGTS'04) 2004.
Modeling Cortical Maps with Topographica 2004
James A. Bednar, Yoonsuck Choe, Judah De Paula, Risto Miikkulainen, Jefferson Provost, and Tal Tversky, Neurocomputing (2004), pp. 1129-1135.
Multiagent Traffic Management: A Reservation-Based Intersection Control Mechanism 2004
Kurt Dresner and Peter Stone, In The Third International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 530-537, July 2004.
Nondefinite vs. Definite Causal Theories 2004
Joohyung Lee, In Proceedings 7th Int'l Conference on Logic Programming and Nonmonotonic Reasoning, pp. 141-153 2004.
Nonmonotonic Causal Theories 2004
Enrico Giunchiglia, Joohyung Lee, Vladimir Lifschitz, Norman McCain and Hudson Turner, Artificial Intelligence, Vol. 153(1--2) (2004), pp. 49-104.
Policy Gradient Reinforcement Learning for Fast Quadrupedal Locomotion 2004
Nate Kohl and Peter Stone, In Proceedings of the {IEEE} International Conference on Robotics and Automation, pp. 2619-2624, May 2004.
Prenatal and Postnatal Development of Laterally Connected Orientation Maps 2004
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 58-60 (2004), pp. 985-992.
Project Halo: Towards a Digital Aristotle 2004
Noah S. Friedland, Paul G. Allen, Gavin Matthews, Michael Witbrock, David Baxter, Jon Curtis, Blake Shepard, Pierluigi Miraglia, Jürgen Angele, Steffen Staab, Eddie Moench, Henrik Oppermann, Dirk Wenke, David Israel, Vinay Chaudhri, Bruce Porter, Ken Barker, James Fan, Shaw Yi Chaw, Peter Yeh, Dan Tecuci, Peter Clark, Artificial Intelligence Magazine, Vol. 25, 4 (2004), pp. 29-47.
Relational Data Mining with Inductive Logic Programming for Link Discovery 2004
Raymond J. Mooney, P. Melville, L. R. Tang, J. Shavlik, I. Dutra and D. Page, Data Mining: Next Generation Challenges and Future DirectionsKargupta, H., Joshi, A., Sivakumar K., and Yesha, Y. (Eds.) (2004), pp. 239--254. AAAI Press.
Relational Markov Networks for Collective Information Extraction 2004
Razvan Bunescu and Raymond J. Mooney, In Proceedings of the ICML-04 Workshop on Statistical Relational Learning and its Connections to Other Fields, Banff, Alberta, July 2004.
Representing the Zoo World and the Traffic World in the language of the Causal Calculator 2004
Varol Akman, Selim T. Erdoğan, Joohyung Lee, Vladimir Lifschitz and Hudson Turner, Artificial Intelligence, Vol. 153(1--2) (2004), pp. 105-140.
RoboCup as an Introduction to CS Research 2004
Peter Stone, In RoboCup-2003: Robot Soccer World Cup VII, Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida (Eds.), Vol. 3020, pp. 284-95, Berlin 2004. Springer Verlag.
SAT-Based Answer Set Programming 2004
Enrico Giunchiglia, Yuliya Lierler, Marco Maratea, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 61-66 2004.
Semi-supervised Clustering with Limited Background Knowledge 2004
Sugato Basu, In Proceedings of the Ninth AAAI/SIGART Doctoral Consortium, pp. 979--980, San Jose, CA, July 2004.
Semi-supervised Clustering: Learning with Limited User Feedback 2004
Sugato Basu, Technical Report, Cornell University.
Semisupervised Clustering for Intelligent User Management 2004
Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney, In Proceedings of the IBM Austin Center for Advanced Studies 5th Annual Austin CAS Conference, Austin, TX, February 2004.
TacTex-03: A Supply Chain Management Agent 2004
David Pardoe and Peter Stone, SIGecom Exchanges: Special Issue on Trading Agent Design and Analysis, Vol. 4, 3 (2004), pp. 19-28.
Text Mining with Information Extraction 2004
Un Yong Nahm, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 217 pages. Also appears as Technical Report UT-AI-TR-04-311.
The Acquisition of Intellectual Expertise: A Computational Model 2004
Elizabeth C. Kaczmarczyk, Risto Miikkulainen, In Proceedings of the 26th Annual Conference of the Cognitive Science Society 2004.
The Champion UT Austin Villa 2003 Simulator Online Coach Team 2004
Gregory Kuhlmann, Peter Stone, and Justin Lallinger, In RoboCup-2003: Robot Soccer World Cup VII 2004.
The Constructivist Learning Architecture: A Model of Cognitive Development for Robust Autonomous Robots 2004
Harold H. Chaput, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Also Technical Report TR-04-34.
The UT Austin Villa 2003 Four-Legged Team 2004
Peter Stone, Kurt Dresner, Selim T. Erdougan, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Ellie Lin, Mohan Sridharan, Daniel Stronger, and Gurushyam Hariharan, In RoboCup-2003: Robot Soccer World Cup VII, Daniel Polani and Brett Browning and Andrea Bonarini and Kazuo Yoshida (Eds.), Berlin 2004. Springer Verlag.
The UT Austin Villa 2004 RoboCup Four-Legged Team: Coming of Age 2004
Peter Stone, Kurt Dresner, Peggy Fidelman, Nicholas K. Jong, Nate Kohl, Gregory Kuhlmann, Mohan Sridharan, and Daniel Stronger, Technical Report UT-AI-TR-04-313, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems 2004
Noah S. Friedland, Paul G. Allen, Michael Witbrock, Gavin Matthews, Nancy Salay, Pierluigi Miraglia, Jurgen Angele, Steffen Staab, David Israel, Vinay Chaudhri, Bruce Porter, Ken Barker, Peter Clark, In The Ninth International Conference on the Principles of Knowledge Representation and Reasoning (KR2004) 2004.
Towards Employing PSRs in a Continuous Domain 2004
Nicholas K. Jong and Peter Stone, Technical Report UT-AI-TR-04-309, The University of Texas at Austin, Department of Computer Sciences, AI Laboratory.
Towards Learning to Ignore Irrelevant State Variables 2004
Nicholas K. Jong and Peter Stone, In The AAAI-2004 Workshop on Learning and Planning in Markov Processes -- Advances and Challenges 2004.
Transfer of Neuroevolved Controllers in Unstable Domains 2004
Faustino J. Gomez and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, Berlin 2004. Springer.
Two Stock-Trading Agents: Market Making and Technical Analysis 2004
Yi Feng, Ronggang Yu, and Peter Stone, In Agent Mediated Electronic Commerce V: Designing Mechanisms and Systems, Peyman Faratin and David C. Parkes and Juan A. Rodriguez-Aguilar and William E. Walsh (Eds.), Vol. 3048, pp. 18-36 200...
Using RoboCup in university-level computer science education 2004
Elizabeth Sklar, Simon Parsons, and Peter Stone, Journal on Educational Resources in Computing, Vol. 4, 2 (2004). Special issue on robotics in undergraduate education. Part 1.
Using Soft-Matching Mined Rules to Improve Information Extraction 2004
Un Yong Nahm and Raymond J. Mooney, In Proceedings of the AAAI-2004 Workshop on Adaptive Text Extraction and Mining (ATEM-2004), pp. 27-32, San Jose, CA, July 2004.
Using the topological skeleton for scalable global metrical map-building 2004
Joseph Modayil, Patrick Beeson and Benjamin Kuipers, In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-04), pp. 1530--1536 2004.
Variational Chernoff bounds for graphical models 2004
P. Ravikumar and J. Lafferty, In Uncertainty in Artificial Intelligence (UAI), pp. 462-469 2004.
Virtual Visual Hulls: Example-Based 3D Shape Inference from a Single Silhouette 2004
K. Grauman, G. Shakhnarovich, and T. Darrell, In The 2nd Workshop on Statistical Methods in Video Processing, in conjunction with ECCV 2004.
A Bayesian Approach to Image-Based Visual Hull Reconstruction 2003
K. Grauman, G. Shakhnarovich, and T. Darrell, In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2003.
A Comparison of String Distance Metrics for Name-Matching Tasks 2003
W. W. Cohen, P. Ravikumar, and S. Fienberg, In In International Joint Conference on Artificial Intelligence (IJCAI) 18, Workshop on Information Integration on the Web 2003.
A Comparison of String Metrics for Matching Names and Records 2003
W. W. Cohen, P. Ravikumar, and S. Fienberg, In International Conference on Knowledge Discovery and Data Mining (KDD) 09, Workshop on Data Cleaning, Record Linkage, and Object Consolidation 2003.
A Taxonomy for Artificial Embryogeny 2003
Kenneth O. Stanley and Risto Miikkulainen, Artificial Life, Vol. 9, 2 (2003), pp. 93-130.
Achieving High-Level Functionality through Evolutionary Complexification 2003
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the AAAI-2003 Spring Symposium on Computational Synthesis, Stanford, CA 2003. AAAI Press.
Acquiring Word-Meaning Mappings for Natural Language Interfaces 2003
Cynthia A. Thompson and Raymond J. Mooney, Journal of Artificial Intelligence Research, Vol. 18 (2003), pp. 1-44.
Active Guidance for a Finless Rocket Using Neuroevolution 2003
Faustino J. Gomez and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 2084-2095, San Francisco 2003. Morgan Kaufmann.
Adaptive Duplicate Detection Using Learnable String Similarity Measures 2003
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2003), pp. 39-48, Washington, DC, August 2003.
Adaptive Name-Matching in Information Integration 2003
Mikhail Bilenko, William W. Cohen, Stephen Fienberg, Raymond J. Mooney, and Pradeep Ravikumar, IEEE Intelligent Systems, Vol. 18, 5 (2003), pp. 16-23.
Associative Anaphora Resolution: A Web-Based Approach 2003
Razvan Bunescu, In Proceedings of the EACL-2003 Workshop on the Computational Treatment of Anaphora, pp. 47-52, Budapest, Hungary 2003.
Bottom-Up Relational Learning of Pattern Matching Rules for Information Extraction 2003
Mary Elaine Califf and Raymond J. Mooney, Journal of Machine Learning Research (2003), pp. 177-210.
Comparing and Unifying Search-Based and Similarity-Based Approaches to Semi-Supervised Clustering 2003
Sugato Basu, Mikhail Bilenko, and Raymond J. Mooney, In Proceedings of the ICML-2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining, pp. 42-49, Washington, DC 2003.
Computing Answer Sets of a Logic Program via Enumeration of SAT Certificates 2003
Yuliya Lierler and Marco Maratea, In 2nd International Workshop on Answer Set Programming 2003.
Concurrent Layered Learning 2003
Shimon Whiteson and Peter Stone, In {AAMAS} 2003: {P}roceedings of the Second International Joint Conference on Autonomous Agents and Multi-Agent Systems, Jeffrey S. Rosenschein and Tuomas Sandholm and Michael Wooldridge and...
Constructing Diverse Classifier Ensembles Using Artificial Training Examples 2003
Prem Melville and Raymond J. Mooney, In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-2003), pp. 505-510, Acapulco, Mexico, August 2003.
Constructivist Learning: A Neural Implementation of the Schema Mechanism 2003
Harold H. Chaput, Benjamin Kuipers and Risto Miikkulainen, In Proceedings of WSOM '03: Workshop for Self-Organizing Maps, Kitakyushu, Japan 2003.
Creating Diverse Ensemble Classifiers 2003
Prem Melville, Technical Report UT-AI-TR-03-306, Department of Computer Sciences, University of Texas at Austin. Ph.D. proposal.
Decision-Theoretic Bidding Based on Learned Density Models in Simultaneous, Interacting Auctions 2003
Peter Stone, Robert E. Schapire, Michael L. Littman, J'anos A. Csirik, and David McAllester, Journal of Artificial Intelligence Research, Vol. 19 (2003), pp. 209-242.
Describing Additive Fluents in Action Language C 2003
Joohyung Lee and Vladimir Lifschitz, In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI-03), pp. 1079--1084 2003.
Employing Trainable String Similarity Metrics for Information Integration 2003
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the IJCAI-03 Workshop on Information Integration on the Web, pp. 67-72, Acapulco, Mexico, August 2003.
Evolving Adaptive Neural Networks with and Without Adaptive Synapses 2003
Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen, In Proceedings of the 2003 Congress on Evolutionary Computation, Piscataway, NJ 2003. IEEE.
Exploiting local perceptual models for topological map-building 2003
Patrick Beeson, Matt MacMahon, Joseph Modayil, Jefferson Provost, Francesco Savelli and Benjamin Kuipers, In IJCAI-2003 Workshop on Reasoning with Uncertainty in Robotics (RUR-03) 2003.
Guest Editors' Introduction: Agents and Markets 2003
Amy Greenwald, Nicholas R. Jennings, and Peter Stone, IEEE Intelligent Systems, Vol. 18, 6 (2003), pp. 12-14.
Incremental Nonmonotonic Parsing through Semantic Self-Organization 2003
Marshall R. Mayberry III, PhD Thesis, Department of Computer Sciences, the University of Texas at Austin. Technical Report AI-TR-04-310.
Incremental Nonmonotonic Parsing through SemanticSelf-Organization 2003
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 25th Annual Conference of the Cognitive Science Society 2003.
Inferring 3D Structure with a Statistical Image-Based Shape Model 2003
K. Grauman, G. Shakhnarovich, and T. Darrell, In IEEE International Conference on Computer Vision (ICCV) 2003.
Integrating Top-down and Bottom-up Approaches in Inductive Logic Programming: Applications in Natural Language Processing and Relational Data Mining 2003
Lappoon R. Tang, PhD Thesis, Department of Computer Sciences, University of Texas.
Learnable Similarity Functions and Their Applications to Record Linkage and Clustering 2003
Mikhail Bilenko, unpublished. Doctoral Dissertation Proposal, University of Texas at Austin.
Learning Concept Drift with a Committee of Decision Trees 2003
Kenneth O. Stanley, Technical Report AI03-302, Department of Computer Sciences, The University of Texas at Austin.
Learning Innate Face Preferences 2003
James A. Bednar and Risto Miikkulainen, Neural Computation, Vol. 15, 7 (2003), pp. 1525-1557.
Learning Predictive State Representations 2003
Satinder Singh, Michael L. Littman, Nicholas K. Jong, David Pardoe, and Peter Stone, In Proceedings of the Twentieth International Conference on Machine Learning, August 2003.
Learning to Extract Proteins and their Interactions from Medline Abstracts 2003
Razvan Bunescu, Ruifang Ge, Rohit J. Kate, Raymond J. Mooney, Yuk Wah Wong, Edward M. Marcotte, and Arun Kumar Ramani, In Proceedings of the ICML-03 Workshop on Machine Learning in Bioinformatics, pp. 46-53, Washington, DC, August 2003.
Loop Formulas for Disjunctive Logic Programs 2003
Joohyung Lee and Vladimir Lifschitz, In Proceedings of International Conference on Logic Programming (ICLP), pp. 451-465 2003.
Machine Learning 2003
Raymond J. Mooney, , McGraw-Hill, New York, NY 2003. McGraw-Hill.
Multiagent Competitions and Research: Lessons from RoboCup and TAC 2003
Peter Stone, In RoboCup-2002: Robot Soccer World Cup VI, Gal A. Kaminka and Pedro U. Lima and Raul Rojas (Eds.), Vol. 2752, pp. 224-237, Berlin 2003. Springer Verlag.
Neuroevolution for Adaptive Teams 2003
Bobby D. Bryant and Risto Miikkulainen, In Proceedings of the 2003 Congress on Evolutionary Computation (CEC 2003), pp. 2194-2201, Piscataway, NJ 2003. IEEE.
On Evaluation and Training-Set Construction for Duplicate Detection 2003
Mikhail Bilenko and Raymond J. Mooney, In Proceedings of the KDD-03 Workshop on Data Cleaning, Record Linkage, and Object Consolidation, pp. 7-12, Washington, DC, August 2003.
Performance Analysis of a Counter-intuitive Automated Stock-Trading Strategy 2003
Ronggang Yu and Peter Stone, In Proceedings of the Fifth International Conference on Electronic Commerce, Pittsburgh, PA, October 2003.
PhD Thesis: Robust Non-Linear Control through Neuroevolution 2003
Faustino J. Gomez, Technical Report AI-TR-03-303, Department of Computer Sciences, University of Texas at Austin.
Qualitative heterogeneous control of higher order systems 2003
Subramanian Ramamoorthy and Benjamin Kuipers, In Hybrid Systems: Computation and Control, Lecture Notes in Computer Science, O. Maler and A. Pnueli (Eds.) 2003. Springer Verlag.
Reconstructing the Evolutionary History of Indo-European Languages Using Answer Set Programming 2003
Esra Erdem, Vladimir Lifschitz, Luay Nakhleh and Donald Ringe, In Practical Aspects of Declarative Languages: 5th International Symposium, pp. 160--176 2003.
Reinforcing a Claim in Commonsense Reasoning 2003
Jonathan Campbell and Vladimir Lifschitz, unpublished. In {em Working Notes of the AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning}.
Robust Non-Linear Control through Neuroevolution 2003
Faustino J. Gomez, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Scaling Up ILP to Large Examples: Results on Link Discovery for Counter-Terrorism 2003
Lappoon R. Tang, Raymond J. Mooney, and Prem Melville, In Proceedings of the KDD-2003 Workshop on Multi-Relational Data Mining (MRDM-2003), pp. 107--121, Washington DC, August 2003.
Self-Organization of Spatiotemporal Receptive Fields and Laterally Connected Direction and Orientation Maps 2003
James A. Bednar and Risto Miikkulainen, Neurocomputing, Vol. 52--54 (2003), pp. 473-480.
Text Mining with Information Extraction 2003
Raymond J. Mooney and Un Yong Nahm, In Multilingualism and Electronic Language Management: Proceedings of the 4th International MIDP Colloquium, W. Daelemans and T. du Plessis and C. Snyman and L. Teck (Eds.), pp. 141-160, Bloemf...
The 2001 Trading Agent Competition 2003
Michael P. Wellman, Amy Greenwald, Peter Stone, and Peter R. Wurman, Electronic Markets, Vol. 13, 1 (2003), pp. 4-12.
The Knowledge Required to Interpret Noun Compounds 2003
James Fan, Ken Barker, Bruce Porter, In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence 2003.
The RoboCup Soccer Server and CMUnited Clients: Implemented Infrastructure for MAS Research 2003
Itsuki Noda and Peter Stone, Autonomous Agents and Multi-Agent Systems, Vol. 7, 1--2 (2003), pp. 101-120.
The Role of Internally Generated Neural Activity in Newborn and Infant Face Preferences 2003
James A. Bednar, In Face Perception in Infancy and Early Childhood, Olivier Pascalis and Alan Slater (Eds.), pp. 133-142, New York 2003. NOVA Science Publishers.
The Role of Postsynaptic Potential Decay Rate in Neural Synchrony 2003
Yoonsuck Choe and Risto Miikkulainen, Neurocomputing, Vol. 52-54 (2003), pp. 707-712.
The skeleton in the cognitive map: a computational and empirical exploration 2003
Benjamin Kuipers, Dan Tecuci and Brian Stankiewicz, Environment and Behavior, Vol. 35, 1 (2003), pp. 80--106.
Tight Logic Programs 2003
Esra Erdem and Vladimir Lifschitz, Theory and Practice of Logic Programming, Vol. 3 (2003), pp. 499-518.
Using Transformations to Improve Semantic Matching 2003
Peter Yeh, Bruce Porter, Ken Barker, In Second International Conference on Knowledge Capture, October 2003.
Utilizing Domain Knowledge in Neuroevolution 2003
James Fan, Raymond Lau, and Risto Miikkulainen, Proceedings of the Twentieth International Conference on Machine Learning (ICML-03, Washington, DC)
Adaptive Control Utilising Neural Swarming 2002
Alex v. E. Conradie, Risto Miikkulainen, and Christiaan Aldrich, In Proceedings of the Genetic and Evolutionary Computation Conference, William B. Langdon and Erick Cantu-Paz and Keith E. Mathias and Rajkumar Roy and David Davis and Riccardo Poli and Karth...
Answer Set Programming and Plan Generation 2002
Vladimir Lifschitz, Artificial Intelligence, Vol. 138 (2002), pp. 39-54.
ATTUnited-2001: Using Heterogeneous Players 2002
Peter Stone, In RoboCup-2001: Robot Soccer World Cup V, Andreas Birk and Silvia Coradeschi and Satoshi Tadokoro (Eds.), Vol. 2377, pp. 495-98, Berlin 2002. Springer Verlag.
Bootstrap learning for place recognition 2002
Benjamin Kuipers and Patrick Beeson, In Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02) 2002.
Content-Boosted Collaborative Filtering for Improved Recommendations 2002
Prem Melville, Raymond J. Mooney, and Ramadass Nagarajan, In Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-02), pp. 187-192, Edmonton, Alberta 2002.
Continual Coevolution Through Complexification 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002), William B. Langdon and Erick Cantu-Paz and Keith E. Mathias and Rajkumar Roy and David Davis and Riccardo Pol...
Cultural Enhancement Of Neuroevolution 2002
Paul H. McQuesten, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI-02-295.
Efficient Evolution Of Neural Network Topologies 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, William B. Langdon and Erick Cantu-Paz and Keith E. Mathias and Rajkumar Roy and David Davis and Riccardo Poli and Karthik...
Efficient Reinforcement Learning Through Evolving Neural Network Topologies 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2002), pp. 9, San Francisco 2002. Morgan Kaufmann.
Eugenic Evolution Utilizing A Domain Model 2002
Matthew Alden, Aard-Jan van Kesteren, and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 279-286 2002.
Evolving Neural Networks Through Augmenting Topologies 2002
Kenneth O. Stanley and Risto Miikkulainen, Evolutionary Computation, Vol. 10, 2 (2002), pp. 99-127.
Extracting Gene and Protein Names from Biomedical Abstracts 2002
Razvan Bunescu, Ruifang Ge, Raymond J. Mooney, Edward Marcotte, and Arun Kumar Ramani, unpublished. Unpublished Technical Note.
Intelligent Process Control Utilizing Symbiotic Memetic Neuro-Evolution 2002
Alex v. E. Conradie, Risto Miikkulainen, and Christiaan Aldrich, In Proceedings of the 2002 Congress on Evolutionary Computation, pp. 6 2002.
Learning to Combine Trained Distance Metrics for Duplicate Detection in Databases 2002
Mikhail Bilenko and Raymond J. Mooney, Technical Report AI 02-296, Artificial Intelligence Laboratory, University of Texas at Austin.
Learning to See: Genetic and Environmental Influences on Visual Development 2002
James A. Bednar, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Also Technical Report AI-TR-02-294.
Mining Soft-Matching Association Rules 2002
Un Yong Nahm and Raymond J. Mooney, In Proceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM-2002), pp. 681-683, McLean, VA, November 2002.
Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation 2002
Robert E. Schapire, Peter Stone, David McAllester, Michael L. Littman, and J'anos A. Csirik, In Proceedings of the Nineteenth International Conference on Machine Learning 2002.
Modeling Directional Selectivity Using Self-Organizing Delay-Adaptation Maps 2002
Tal Tversky and Risto Miikkulainen, Neurocomputing, Vol. 44--46 (2002), pp. 679--684. Also in J. M. Bower (editor), Computational Neuroscience: Trends in Research, 2002 (CNS*01, Pacific Grove, CA). New York: Elsevier.
Modeling Large Cortical Networks With Growing Self-Organizing Maps 2002
James A. Bednar, Amol Kelkar, and Risto Miikkulainen, Neurocomputing, Vol. 44--46 (2002), pp. 315-321.
Neonatal Learning Of Faces: Environmental And Genetic Influences 2002
James A. Bednar and Risto Miikkulainen, In Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 107-112 2002.
Neuroevolution through Augmenting Topologies Applied to Evolving Neural Networks to Play Othello 2002
Timothy Andersen, Technical Report HR-02-01, Department of Computer Sciences, The University of Texas at Austin.
Numerical Optimization With Neuroevolution 2002
Brian Greer, Henri Hakonen, Risto Lahdelma, and Risto Miikkulainen, In Proceedings of the 2002 Congress on Evolutionary Computation, pp. 361-401, Piscataway, NJ 2002. IEEE. Undergraduate Thesis, Department of Computer Sciences, The University of Texas at Aust...
On Calculational Proofs 2002
Vladimir Lifschitz, Annals of Pure and Applied Logic, Vol. 113 (2002), pp. 207-224.
Property-Based Feature Engineering and Selection 2002
Noppadon Kamolvilassatian, Masters Thesis, Department of Computer Sciences, University of Texas at Austin. 85 pages.
Qualitative modeling and heterogeneous control of global system behavior 2002
Benjamin Kuipers and Subramanian Ramamoorthy, In Hybrid Systems: Computation and Control, Lecture Notes in Computer Science, C. J. Tomlin and M. R. Greenstreet (Eds.) 2002. Springer Verlag.
Relational Data Mining with Inductive Logic Programming for Link Discovery 2002
Raymond J. Mooney, Prem Melville, Lappoon R. Tang, Jude Shavlik, Inês de Castro Dutra, David Page, and Vítor Santos Costa, In Proceedings of the National Science Foundation Workshop on Next Generation Data Mining, Baltimore, MD, November 2002.
Self-enforcing Strategic Demand Reduction 2002
Paul S. A. Reitsma, Peter Stone, J'anos A. Csirik, and Michael L. Littman, In Agent Mediated Electronic Commerce IV: Designing Mechanisms and Systems, Vol. 2531, pp. 289-306 2002. Springer Verlag.
Semi-supervised Clustering by Seeding 2002
Sugato Basu, Arindam Banerjee, and Raymond J. Mooney, In Proceedings of 19th International Conference on Machine Learning (ICML-2002), pp. 19-26 2002.
Text and Discourse Understanding: The DISCERN System 2002
Risto Miikkulainen, In A Handbook of Natural Language Processing: Techniques and Applications for the Processing of Language as Text, R. Dale, H. Moisl and H. Somers (Eds.), pp. 905--919, New York 2002.
Text Mining with Information Extraction 2002
Un Yong Nahm and Raymond J. Mooney, In Proceedings of the AAAI 2002 Spring Symposium on Mining Answers from Texts and Knowledge Bases, pp. 60-67, Stanford, CA, March 2002.
The Dominance Tournament Method of Monitoring Progress in Coevolution 2002
Kenneth O. Stanley and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference ({GECCO}-2002) Workshop Program, pp. 7, San Francisco 2002. Morgan Kaufmann.
Theory and Applications of Answer Set Programming 2002
Esra Erdem , PhD Thesis, University of Texas at Austin.
Towards a general theory of topological maps 2002
Emilio Remolina and Benjamin Kuipers, Technical Report TR-02-293, University of Texas at Austin Artificial Intelligence Lab.
Two Approaches to Handling Noisy Variation in Text Mining 2002
Un Yong Nahm, Mikhail Bilenko, and Raymond J. Mooney, In Papers from the Nineteenth International Conference on Machine Learning (ICML-2002) Workshop on Text Learning, pp. 18-27, Sydney, Australia, July 2002.
A Library of Generic Concepts for Composing Knowledge Bases 2001
Ken Barker, Bruce Porter, and Peter Clark, In Proceedings of First International Conference on Knowledge Capture, pp. 14-21 2001.
A logical account of causal and topological maps 2001
Emilio Remolina, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
A Model Of Infant Causal Perception And Its Development 2001
Harold H. Chaput and Leslie B. Cohen, In Proceedings of the 23rd Annual Conference of the Cognitive Science Society, pp. 182-187 2001.
A Neuroevolution Method For Dynamic Resource Allocation On A Chip Multiprocessor 2001
Faustino J. Gomez, Doug Burger, and Risto Miikkulainen, In Proceedings of the {INNS-IEEE} International Joint Conference on Neural Networks, pp. 2355-2361, Piscataway, NJ 2001. IEEE.
A Social Reinforcement Learning Agent 2001
Charles Lee Isbell, Christian R. Shelton, Michael Kearns, Satinder Singh, and Peter Stone, In Proceedings of the Fifth International Conference on Autonomous Agents, pp. 377--384 2001.
Abrupt And Gradual Sound Change In An Expanding Lexicon 2001
Melissa A. Redford and Risto Miikkulainen, Technical Report AI01-289, Department of Computer Sciences, The University of Texas at Austin.
Additive Fluents 2001
Joohyung Lee and Vladimir Lifschitz, unpublished. In {em Working Notes of the AAAI Spring Symposium on Answer Set Programming}.
An Architecture for Action Selection in Robotic Soccer 2001
Peter Stone and David McAllester, In Proceedings of the Fifth International Conference on Autonomous Agents, Elisabeth Andre and Sandip Sen and Claude Frasson and Jörg P. Müller (Eds.), pp. 316-323, New York, NY 2001. ACM Pres...
Applying ESP And Region Specialists To Neuro-Evolution For Go 2001
Andres Santiago Perez-Bergquist, Technical Report TR-01-24, Department of Computer Science, University of Texas at Austin.
ATT-CMUnited-2000: Third Place Finisher in the RoboCup-2000 Simulator League 2001
Patrick Riley, Peter Stone, David McAllester, and Manuela Veloso, In RoboCup-2000: Robot Soccer World Cup IV, P. Stone and T. Balch and G. Kraetzschmar (Eds.), Vol. 2019, Berlin 2001. Springer Verlag.
ATTac-2000: An Adaptive Autonomous Bidding Agent 2001
Peter Stone, Michael L. Littman, Satinder Singh, and Michael Kearns, Journal of Artificial Intelligence Research, Vol. 15 (2001), pp. 189-206.
Autonomous Bidding Agents in the Trading Agent Competition 2001
Amy Greenwald and Peter Stone, IEEE Internet Computing, Vol. 5, 2 (2001), pp. 52-60.
Co-Evolving A Go-Playing Neural Network 2001
Alex Lubberts and Risto Miikkulainen, In Coevolution: {T}urning Adaptive Algorithms Upon Themselves, Birds-of-a-Feather Workshop, Genetic and Evolutionary Computation Conference ({GECCO}-2001), pp. 6 2001.
Cobot in LambdaMOO: A Social Statistics Agent 2001
Charles Lee Isbell Jr., Michael Kearns, Dave Kormann, Satinder Singh, and Peter Stone, In Proceedings of the Seventeenth National Conference on Artificial Intelligence, pp. 36--41 2001.
Communication via Eye Blinks: Detection and Duration Analysis in Real Time 2001
K. Grauman, M. Betke, J. Gips, and G. Bradski, In IIEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2001.
Computational Perceptual Attention 2001
Micheal Scott Hewett, PhD Thesis, Department of Computer Science, University of Texas at Austin.
Constrained Emergence Of Universals And Variation In Syllable Systems 2001
Melissa A. Redford, Chun Chi Chen, and Risto Miikkulainen, Language and Speech (2001), pp. 27-56. Manuscript.
Content-Boosted Collaborative Filtering 2001
Prem Melville, Raymond J. Mooney, and Ramadass Nagarajan, In Proceedings of the SIGIR-2001 Workshop on Recommender Systems, New Orleans, LA, September 2001.
Cooperative Coevolution Of Multi-Agent Systems 2001
Chern Han Yong and Risto Miikkulainen, Technical Report AI07-338, Department of Computer Sciences, The University of Texas at Austin.
Creating Melodies With Evolving Recurrent Neural Networks 2001
Chun-Chi J. Chen and Risto Miikkulainen, In Proceedings of the {INNS-IEEE} International Joint Conference on Neural Networks, pp. 2241-2246, Piscataway, NJ 2001. IEEE.
ELIXIR: A Library for Writing Wrappers in Java 2001
Edward Wild, Undergraduate Honor Thesis, Department of Computer Sciences, University of Texas at Austin.
Evaluating the Novelty of Text-Mined Rules using Lexical Knowledge 2001
Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, and Joydeep Ghosh, In Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001), pp. 233-239, San Francisco, CA 2001.
Evolving Populations Of Expert Neural Networks 2001
Joseph Bruce and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference, pp. 251-257, San Francisco, CA 2001. Morgan Kaufmann.
Fages' Theorem for Programs with Nested Expressions 2001
Esra Erdem and Vladimir Lifschitz, In Proceedings of International Conference on Logic Programming (ICLP), pp. 242-254 2001.
FAucS: An FCC Spectrum Auction Simulator for Autonomous Bidding Agents 2001
J'anos A. Csirik, Michael L. Littman, Satinder Singh, and Peter Stone, In Electronic Commerce: Proceedings of the Second International Workshop, Ludger Fiege and Gero Mühl and Uwe Wilhelm (Eds.), pp. 139-151, Heidelberg, Germany 2001. Springer Verlag.
From Word Stream To Gestalt: A Direct Semantic Parse For Complex Sentences 2001
Bobby D. Bryant and Risto Miikkulainen, Technical Report AI98-274, AI Lab, University of Texas at Austin.
Implicit Negotiation in Repeated Games 2001
Michael L. Littman and Peter Stone, In Proceedings of The Eighth International Workshop on Agent Theories, Architectures, and Languages (ATAL-2001), pp. 393-404, August 2001.
Keeping the Ball from CMUnited-99 2001
David McAllester and Peter Stone, In RoboCup-2000: Robot Soccer World Cup IV, Peter Stone and Tucker Balch and Gerhard Kraetzschmar (Eds.), Vol. 2019, pp. 333-338, Berlin 2001. Springer Verlag.
Layered Disclosure: Revealing Agents' Internals 2001
Patrick Riley, Peter Stone, and Manuela Veloso, In Intelligent Agents VII. Agent Theories, Architectures, and Languages --- 7th.~International Workshop, ATAL-2000, Boston, MA, USA, July 7--9, 2000, Proceedings, C. Castelfranchi and Y. Lesper...
Learning from uninterpreted experience in the SSH 2001
Benjamin Kuipers, Patrick Beeson, Joseph Modayil and Jefferson Provost, In AAAI Spring Symposium Series, Learning Grounded Representations, Stanford, CA 2001.
Mining Soft-Matching Rules from Textual Data 2001
Un Yong Nahm and Raymond J. Mooney, In Proceedings of the 18th International Joint Conference on Artificial Intelligence 2001.
Numerical Optimization with Neuroevolution 2001
Brian Greer, Technical Report TR-01-49, Department of Computer Science, The University of Texas at Austin.
Perceptual Grouping In A Self-Organizing Map Of Spiking Neurons 2001
Yoonsuck Choe, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 133. Technical Report AI01-292.
Post-Piagetian constructivism for grounded knowledge acquisition 2001
Harold H. Chaput, In Proceedings of the AAAI Spring Symposium Series on Grounded Knoweldge, Palo Alto, CA 2001.
Representing Roles and Purpose 2001
James Fan, Ken Barker, Bruce Porter, Peter Clark, In First International Conference on Knowledge Capture, October 2001.
RoboCup-2000: The Fourth Robotic Soccer World Championships 2001
Peter Stone, Minoru Asada, Tucker Balch, Raffaelo D'Andrea, Masahiro Fujita, Bernhard Hengst, Gerhard Kraetzschmar, Pedro Lima, Nuno Lau, Henrik Lund, Daniel Polani, Paul Scerri, Satoshi Tadokoro, Thilo Weigel, and Gordon Wyeth, AI Magazine, Vol. 22, 1 (2001).
Scaling Self-Organizing Maps To Model Large Cortical Networks 2001
James A. Bednar, Amol Kelkar, and Risto Miikkulainen, Neuroinformatics (2001), pp. 275-302.
Semantic Effect On Episodic Associations 2001
Yaron Silberman, Risto Miikkulainen, and Shlomo Bentin, In Proceedings of the 23rd Annual Conference of the Cognitive Science Society, pp. 934-939 2001.
Strongly Equivalent Logic Programs 2001
Vladimir Lifschitz, David Pearce and Agustin Valverde, ACM Transactions on Computational Logic, Vol. 2 (2001), pp. 526-541.
Text Mining with Information Extraction 2001
Un Yong Nahm, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
The skeleton in the cognitive map: a computational hypothesis 2001
Benjamin Kuipers, In Space Syntax: Proceedings of the Third International Symposium, J. Peponis, J. Wineman and S. Bafna (Eds.), pp. 10.1--10.7 2001.
Toward bootstrap learning for place recognition 2001
Benjamin Kuipers and Patrick Beeson, AAAI Technical Report FS-01-01, ISBN 1-57735-135-5
Toward Learning the Causal Layer of the Spatial Semantic Hierarchy using SOMs 2001
Jefferson Provost, Patrick Beeson, and Benjamin J. Kuipers, In AAAI Spring Symposium Series, Learning Grounded Representations 2001.
Using Lexical Knowlege to Evaluate the Novelty of Rules Mined from Text 2001
Sugato Basu, Raymond J. Mooney, Krupakar V. Pasupuleti, and Joydeep Ghosh, In Proceedings of NAACL 2001 Workshop on WordNet and Other Lexical Resources: Applications, Extensions and Customizations, pp. 144--149, Pittsburg, PA, June 2001.
Using Multiple Clause Constructors in Inductive Logic Programming for Semantic Parsing 2001
Lappoon R. Tang and Raymond J. Mooney, In Proceedings of the 12th European Conference on Machine Learning, pp. 466-477, Freiburg, Germany 2001.
A Mutually Beneficial Integration of Data Mining and Information Extraction 2000
Un Yong Nahm and Raymond J. Mooney, In Proceedings of the Seventeenth National Conference on Artificial Intelligence (AAAI-00), pp. 627-632, Austin, TX, July 2000.
A Self-Organizing Neural Network For Contour Integration Through Synchronized Firing 2000
Yoonsuck Choe and Risto Miikkulainen, Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000, Austin, TX), 123-128. Cambridge, MA: MIT Press, 2000
Automated Construction of Database Interfaces: Integrating Statistical and Relational Learning for Semantic Parsing 2000
Lappoon R. Tang and Raymond J. Mooney, In Proceedings of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora(EMNLP/VLC-2000), pp. 133-141, Hong Kong, October 2000.
Automatic Music Composition using Genetic Algorithm and Neural Networks: A Constrained Evolution Approach 2000
Chun-Chi Chen, Technical Report HR-00-02, Department of Computer Sciences, The University of Texas at Austin.
Book review: M. Shanahan, Solving the Frame Problem 2000
Vladimir Lifschitz, Artificial Intelligence, Vol. 123 (2000), pp. 265-268.
Content-Based Book Recommending Using Learning for Text Categorization 2000
Raymond J. Mooney and Loriene Roy, In Proceedings of the Fifth ACM Conference on Digital Libraries, pp. 195-204, San Antonio, TX, June 2000.
Cooperative Coevolution of Multi-Agent Systems 2000
Chern Han Yong, Technical Report HR-00-01, Department of Computer Sciences, The University of Texas at Austin.
Defining and Using Ideal Teammate and Opponent Models 2000
Peter Stone, Patrick Riley, and Manuela Veloso, In Proceedings of the Twelfth Annual Conference on Innovative Applications of Artificial Intelligence 2000.
Effects Of Presynaptic And Postsynaptic Resource Redistribution In Hebbian Weight Adaptation 2000
Yoonsuck Choe, Risto Miikkulainen, and Lawrence K. Cormack, Neurocomputing, Vol. 32--33 (2000), pp. 77-82.
Eugenic Neuro-Evolution For Reinforcement Learning 2000
Daniel Polani and Risto Miikkulainen, In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000), pp. 1041-1046, San Francisco 2000. Morgan Kaufmann.
Fages' Theorem and Answer Set Programming 2000
Yuliya Lierler, Esra Erdem and Vladimir Lifschitz, In Proceedings of International Workshop on Nonmonotonic Reasoning (NMR), pp. 33-35 2000. Springer.
Getting to the Airport: the Oldest Planning Problem in AI 2000
Vladimir Lifschitz, Norman McCain, Emilio Remolina and Armando Tacchella, In Logic-Based Artificial Intelligence, Jack Minker (Eds.), pp. 147-165 2000. Kluwer.
Hebbian Learning And Temporary Storage In The Convergence-Zone Model Of Episodic Memory 2000
Michael Howe and Risto Miikkulainen, Neurocomputing, Vol. 32--33 (2000), pp. 817--821. Also J. M. Bower (editor), Computational Neuroscience: Trends in Research, 2000 (CNS*99, Pittsburgh, PA). New York: Plenum Press..
Integrating Abduction and Induction in Machine Learning 2000
Raymond J. Mooney, In Abduction and Induction, P. A. Flach and A. C. Kakas (Eds.), pp. 181-191 2000. Kluwer Academic Publishers.
Integrating Statistical and Relational Learning for Semantic Parsing: Applications to Learning Natural Language Interfaces for Databases 2000
Lappoon R. Tang, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Interactions of Abstractions in Programming 2000
Gordon S. Novak Jr., In Lecture Notes in Artificial Intelligence, Vol. 1864, pp. 185--201 2000. Springer-Verlag. ISBN 3-540-67839-5.
Internally-Generated Activity, Non-Episodic Memory, and Emotional Salience in Sleep 2000
James A. Bednar, Behavioral and Brain SciencesS. Harnad and E. Pace-Schott and M. Blagrove and M. Solms (Eds.) (2000), pp. 119-120. Cambridge University Press. Commentary on the 'Sleep and Dreaming' issue..
Layered Learning 2000
Peter Stone and Manuela Veloso, In Machine Learning: ECML 2000 (Proceedings of the Eleventh European Conference on Machine Learning), Ramon Lopez de Mantaras and Enric Plaza (Eds.), pp. 369-381, Barcelona,Catalonia,Spain, May...
Layered Learning in Multiagent Systems: A Winning Approach to Robotic Soccer 2000
Peter Stone, No other information
Learning for Semantic Interpretation: Scaling Up Without Dumbing Down 2000
Raymond J. Mooney, In Workshop Notes for the Workshop on Learning Language in Logic, pp. 7-15, Bled, Slovenia 2000.
Missionaries and Cannibals in the Causal Calculator 2000
Vladimir Lifschitz, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), pp. 85-96 2000.
Multiagent Systems: A survey from a machine learning perspective 2000
Peter Stone and Manuela Veloso, Autonomous Robots, Vol. 8, 3 (2000), pp. 345-383.
Neuro-Evolution And Natural Deduction 2000
Nirav S. Desai and Risto Miikkulainen, In Proceedings of The First {IEEE} Symposium on Combinations of Evolutionary Computation and Neural Networks, pp. 64-69, Piscataway, NJ 2000. IEEE.
Online Interactive Neuro-Evolution 2000
Adrian Agogino, Kenneth O. Stanley, and Risto Miikkulainen, Neural Processing Letters (2000), pp. 29-38.
Overview of RoboCup-99 2000
Silvia Coradeschi, Lars Karlsson, Peter Stone, Tucker Balch, Gerhard Kraetzschmar, and Minoru Asada, AI Magazine, Vol. 21, 3 (2000).
Self-Organization Of Innate Face Preferences: Could Genetics Be Expressed Through Learning? 2000
James A. Bednar and Risto Miikkulainen, In Proceedings of the 17th National Conference on Artificial Intelligence and the 12th Annual Conference on Innovative Applications of Artificial Intelligence, pp. 117-122 2000.
The CMUnited-97 Robotic Soccer Team: Perception and Multi-agent Control 2000
Manuela Veloso, Peter Stone, and Kwun Han, Robotics and Autonomous Systems, Vol. 29, 2-3 (2000), pp. 133-143.
The CMUnited-99 Champion Simulator Team 2000
Peter Stone, Patrick Riley, and Manuela Veloso, In RoboCup-99: Robot Soccer World Cup III, M. Veloso and E. Pagello and H. Kitano (Eds.), Vol. 1856, pp. 35-48, Berlin 2000. Springer Verlag.
The Spatial Semantic Hierarchy 2000
Benjamin Kuipers, Artificial Intelligence, 1-2 (2000), pp. 191-233.
Tilt Aftereffects In A Self-Organizing Model Of The Primary Visual Cortex 2000
James A. Bednar and Risto Miikkulainen, Neural Computation, Vol. 12 (2000), pp. 1721-1740.
TPOT-RL Applied to Network Routing 2000
Peter Stone, In Proceedings of the Seventeenth International Conference on Machine Learning, pp. 935-942 2000.
Using Information Extraction to Aid the Discovery of Prediction Rules from Text 2000
Un Yong Nahm and Raymond J. Mooney, In Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining (KDD-2000) Workshop on Text Mining, pp. 51--58, Boston, MA, August 2000.
Wire Routing and Satisfiability Planning 2000
Esra Erdem, Vladimir Lifschitz and Martin Wong, In Proceedings of International Conference on Computational Logic, pp. 822-836 2000.
Action Languages, Answer Sets and Planning 1999
Vladimir Lifschitz, In The Logic Programming Paradigm: a 25-Year Perspective, pp. 357-373 1999. Springer Verlag.
Action Languages, Temporal Action Logics and the Situation Calculus 1999
Enrico Giunchiglia and Vladimir Lifschitz, In Working Notes of the IJCAI-99 Workshop on Nonmonotonic Reasoning, Action, and Change 1999.
Active Learning for Natural Language Parsing and Information Extraction 1999
Cynthia A. Thompson, Mary Elaine Califf and Raymond J. Mooney, In Proceedings of the Sixteenth International Conference on Machine Learning (ICML-99), pp. 406-414, Bled, Slovenia, June 1999.
Answer Set Planning 1999
Vladimir Lifschitz, In Proceedings ICLP-99, pp. 23-37 1999.
Anticipation as a Key for Collaboration in a Team of Agents: A Case Study in Robotic Soccer 1999
Manuela Veloso, Peter Stone, and Michael Bowling, In Proceedings of SPIE Sensor Fusion and Decentralized Control in Robotic Systems II, Paul S. Schenker and Gerard T. McKee (Eds.), Vol. 3839, pp. 134-143, Bellingham, WA, September 1999. SPIE.
Automatic Construction of Semantic Lexicons for Learning Natural Language Interfaces 1999
Cynthia A. Thompson and Raymond J. Mooney, In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), pp. 487-493, Orlando, FL, July 1999.
Confidence Based Dual Reinforcement Q-Routing: An Adaptive On-Line Routing Algorithm 1999
Shailesh Kumar and Risto Miikkulainen, In 16th International Joint Conference on Artificial Intelligence (IJCAI-99), pp. 758--763, Stockholm, Sweden 1999. San Francisco, CA: Kaufmann.
Content-Based Book Recommending Using Learning for Text Categorization 1999
Raymond J. Mooney and Loriene Roy, In Proceedings of the SIGIR-99 Workshop on Recommender Systems: Algorithms and Evaluation, Berkeley, CA, August 1999.
Disambiguation And Grammar As Emergent Soft Constraints 1999
Risto Miikkulainen and Marshall R. Mayberry III, In Workshop on Thought and Language, Brian J. MacWhinney (Eds.), pp. 20-31, Iizuka, Japan 1999. Department of Artificial Intelligence, Kyushu Institute of Technology.
Modeling The Self-Organization Of Directional Selectivity In The Primary Visual Cortex 1999
Igor Farkas and Risto Miikkulainen, In Proceedings of the Ninth International Conference on Artificial Neural Networks, Erkki Oja and Samuel Kaski (Eds.), pp. 251-256, Amsterdam 1999. Elsevier.
Nested Expressions in Logic Programs 1999
Vladimir Lifschitz, Lappoon R. Tang and Hudson Turner, Annals of Mathematics and Artificial Intelligence, Vol. 25 (1999), pp. 369-389.
Relational Learning of Pattern-Match Rules for Information Extraction 1999
Mary Elaine Califf and Raymond J. Mooney, In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI-99), pp. 328-334, Orlando, FL, July 1999.
Representing Transition Systems by Logic Programs 1999
Vladimir Lifschitz and Hudson Turner, In Proceedings of International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR), pp. 92-106 1999.
SARDSRN: A Neural Network Shift-Reduce Parser 1999
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 16th Annual International Joint Conference on Artificial Intelligence (IJCAI-99), pp. 820-825, Stockholm, Sweden 1999. San Francisco, CA: Kaufmann.
Solving Non-Markovian Control Tasks With Neuroevolution 1999
Faustino J. Gomez and Risto Miikkulainen, In Proceedings of the International Joint Conference on Artificial Intelligence, pp. 1356-1361, San Francisco, CA 1999. Kaufmann.
Success of Default Logic 1999
Vladimir Lifschitz, In Logical Foundations for Cognitive Agents: Contributions in Honor of Ray Reiter, Levesque, Hector and Pirri, Fiora (Eds.), pp. 208-212 1999. Springer.
Task Decomposition, Dynamic Role Assignment, and Low-Bandwidth Communication for Real-Time Strategic Teamwork 1999
Peter Stone and Manuela Veloso, Artificial Intelligence, Vol. 110, 2 (1999), pp. 241-273.
Team-Partitioned, Opaque-Transition Reinforcement Learning 1999
Peter Stone and Manuela Veloso, In RoboCup-98: Robot Soccer World Cup II, Minoru Asada and Hiroaki Kitano (Eds.), Vol. 1604, pp. 261-72, Berlin 1999. Springer Verlag. Also in Proceedings of the Third International Confe...
The CMUnited-98 Champion Simulator Team 1999
Peter Stone, Manuela Veloso, and Patrick Riley, In RoboCup-98: Robot Soccer World Cup II, M. Asada and H. Kitano (Eds.), Vol. 1604, pp. 61-76 1999. Springer Verlag.
The CMUnited-98 Champion Small Robot Team 1999
Manuela Veloso, Michael Bowling, Sorin Achim, Kwun Han, and Peter Stone, In RoboCup-98: Robot Soccer World Cup II, Minoru Asada and Hiroaki Kitano (Eds.), Vol. 1604, pp. 77-92, Berlin 1999. Springer Verlag.
Transformations of Logic Programs Related to Causality and Planning 1999
Esra Erdem and Vladimir Lifschitz, In Logic Programming and Non-monotonic Reasoning: Proceedings Fifth Int'l Conf. (Lecture Notes in Artificial Intelligence 1730), pp. 107-116 1999.
Using a Sequential SOM to Parse Long-Term Dependencies 1999
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 21st Annual Conference of the Cognitive Science Society, Martin Hahn and Scott C. Stoness (Eds.), pp. 367-372 1999. Hillsdale, NJ: Erlbaum.
Using HTML Structure and Linked Pages to Improve Learning for Text Categorization 1999
Michael B. Cline, Technical Report AI 98-270, Department of Computer Sciences, University of Texas at Austin. Undergraduate Honors Thesis.
2-D Pole Balancing With Recurrent Evolutionary Networks 1998
Faustino Gomez and Risto Miikkulainen, In Proceedings of the International Conference on Artificial Neural Networks (ICANN-98), pp. 425-430, Skovde, Sweden 1998. Berlin, New York: Springer.
A Layered Approach to Learning Client Behaviors in the RoboCup Soccer Server 1998
Peter Stone and Manuela Veloso, Applied Artificial Intelligence, Vol. 12 (1998), pp. 165-188.
A Self-Organizing Neural Network Model of the Primary Visual Cortex 1998
Risto Miikkulainen, James Bednar, Yoonsuck Choe, and Joseph Sirosh, In Proceedings of the Fifth International Conference on Neural Information Processing (ICONIP'98), Volume 2, S. Usui, T. Omori (Eds.), pp. 815-818, Kitakyushu, Japan 1998.
Action Languages 1998
Michael Gelfond and Vladimir Lifschitz, Electronic Transactions on Artificial Intelligence, Vol. 3 (1998), pp. 195-210.
Advantages of Decision Lists and Implicit Negatives in Inductive Logic Programming 1998
Mary Elaine Califf and Raymond J. Mooney, New Generation Computing, Vol. 16, 3 (1998), pp. 263-281.
An Action Language Based on Causal Explanation: preliminary report 1998
Enrico Giunchiglia and Vladimir Lifschitz, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 623-630 1998. AAAI Press.
An Experimental Comparison of Genetic Programming and Inductive Logic Programming on Learning Recursive List Functions 1998
Lappoon R. Tang, Mary Elaine Califf, and Raymond J. Mooney, Technical Report AI 98-271, Artificial Intelligence Lab, University of Texas at Austin.
Book Recommending Using Text Categorization with Extracted Information 1998
Raymond J. Mooney, Paul N. Bennett, and Loriene Roy, In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI-98)"-REC-WKSHP98, year="1998, pp. 70-74, Madison, WI 1998.
Boundary region relations 1998
Emilio Remolina and Benjamin Kuipers, In Cognitive Robotics, Papers from the 1998 AAAI Fall Symposium, pp. 117--124, Menlo Park, CA 1998. AAAI Press. Technical report FS-98-02.
Causal Action Theories and Satisfiability Planning 1998
Hudson Turner, PhD Thesis, University of Texas at Austin.
Confidence Based Dual Reinforcement Q-Routing: An On-Line Adaptive Network Routing Algorithm 1998
Shailesh Kumar, Masters Thesis, Department of Computer Sciences, the University of Texas at Austin.. 108. Technical Report AI-98-267.
Confidence Based Q-Routing: An On-Line Adaptive Network Routing Algorithm 1998
Shailesh Kumar and Risto Miikkulainen, Smart Engineering Systems: Neural Networks, Fuzzy Logic, Data Mining, and Evolutionary ProgrammingC. H. Dagli and M. Akay and O. Ersoy and B. R. Fernandez and A. Smith (Eds.), Vol. 8 (1998).
Eugenic Evolution For Combinatorial Optimization 1998
John W. Prior, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 126. Technical Report AI98-268.
Evolving Hierarchical Neural Networks to Play Go 1998
Todd Greer, Technical Report HR-94-01, Department of Computer Science, The University of Texas at Austin.
Evolving Neural Networks To Play Go 1998
Norman Richards, David Moriarty, and Risto Miikkulainen, Applied IntelligenceThomas B{"a}ck (Eds.) (1998), pp. 768-775. San Francisco, CA: Morgan Kaufmann.
Hierarchical Evolution Of Neural Networks 1998
David E. Moriarty and Risto Miikkulainen, In Proceedings of the 1998 IEEE Conference on Evolutionary Computation (ICEC98), pp. 428-433, Anchorage, AK 1998. Piscataway, NJ: IEEE.
Integrating vision and spatial reasoning for assistive navigation 1998
W. S. Gribble, R. L. Browning, M. Hewett, E. Remolina and Benjamin J. Kuipers, In Assistive Technology and Artificial Intelligence, V. Mittal and H. Yanco and J. Aronis and R. Simpson (Eds.), Berlin 1998. Springer.
Intrusion Detection With Neural Networks 1998
Jake Ryan, Meng-Jang Lin, and Risto Miikkulainen, In Advances in Neural Information Processing Systems 10, Michael I. Jordan and Michael J. Kearns and Sara A. Solla (Eds.), pp. 943-949, Department of Computer Sciences, The University of Texas ...
Modeling The Emergence Of Syllable Systems 1998
Melissa A. Redford, Chun Chi Chen, and Risto Miikkulainen, In Proceedings of the 20th Annual Conference of the Cognitive Science Society, Morton Ann Gernsbacher and Sharon J. Derry (Eds.), pp. 882-886 1998. Hillsdale, NJ: Erlbaum.
Navigation and mapping in large scale space 1998
Benjamin J. Kuipers and T. Levitt, AI Magazine, Vol. 9, 2 (1998), pp. 25--43. Reprinted in Advances in Spatial Reasoning, Volume 2, Su-shing Chen (Ed.), Norwood NJ: Ablex Publishing, 1990.
Pattern-Generator-Driven Development In Self-Organizing Models 1998
James A. Bednar and Risto Miikkulainen, In Computational Neuroscience: Trends in Research, 1998, pp. 317-323 1998.
Relational Learning of Pattern-Match Rules for Information Extraction 1998
Mary Elaine Califf and Raymond J. Mooney, In Proceedings of AAAI Spring Symposium on Applying Machine Learning to Discourse Processing, pp. 6-11, Standford, CA, March 1998.
Relational Learning Techniques for Natural Language Information Extraction 1998
Mary Elaine Califf, PhD Thesis, Department of Computer Sciences, University of Texas. 142 pages. Also appears as Artificial Intelligence Laboratory Technical Report AI 98-276.
Satisfiability Planning with Causal Theories 1998
Norman McCain and Hudson Turner, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), Cohn, Anthony and Schubert, Lenhart and Shapiro, Stuart (Eds.), pp. 212-223 1998.
Self-Organization And Segmentation In A Laterally Connected Orientation Map Of Spiking Neurons 1998
Yoonsuck Choe and Risto Miikkulainen, Neurocomputing (1998), pp. 139-157.
Semantic Lexicon Acquisition for Learning Natural Language Interfaces 1998
Cynthia Ann Thompson, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 101 pages. Also appears as Technical Report AI 99-278, Artificial Intelligence Lab, University of Texas at Austin.
Semantic Lexicon Acquisition for Learning Natural Language Interfaces 1998
Cynthia A. Thompson and Raymond J. Mooney, In Proceedings of the Sixth Workshop on Very Large Corpora, Montreal, Quebec, Canada, August 1998. Also available as TR AI 98-273, Artificial Intelligence Lab, University of Texas at Austin, M...
Situation Calculus and Causal Logic 1998
Vladimir Lifschitz, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), Cohn, Anthony and Schubert, Lenhart and Shapiro, Stuart (Eds.), pp. 536-546 1998.
Text Categorization Through Probabilistic Learning: Applications to Recommender Systems 1998
Paul N. Bennett, unpublished. Honors thesis, Department of Computer Sciences, The University of Texas at Austin.
The CMUnited-97 Simulator Team 1998
Peter Stone and Manuela Veloso, In RoboCup-97: Robot Soccer World Cup I, Hiroaki Kitano (Eds.), Vol. 1395, pp. 387-397, Berlin 1998. Springer Verlag.
The CMUnited-97 Small-Robot Team 1998
Manuela Veloso, Peter Stone, Kwun Han, and Sorin Achim, In RoboCup-97: Robot Soccer World Cup I, Hiroaki Kitano (Eds.), Vol. 1395, pp. 242-256, Berlin 1998. Springer Verlag.
The Impact of Perception on Agent Architectures 1998
Micheal Hewett, In Proceedings of the AAAI-98 Workshop on Software Tools for Developing Agents 1998.
The RoboCup Physical Agent Challenge: Phase-I 1998
Minoru Asada, Yasuo Kuniyoshi, Alexis Drogoul, Hajime Asama, Maja Mataric, Dominique Duhaut, Peter Stone, and Hiroaki Kitano, Applied Artificial Intelligence, Vol. 12 (1998), pp. 251-263.
Theory Refinement for Bayesian Networks with Hidden Variables 1998
Sowmya Ramachandran and Raymond J. Mooney, In Proceedings of the Fifteenth International Conference on Machine Learning (ICML-98), pp. 454--462, Madison, WI, July 1998.
Theory Refinement of Bayesian Networks with Hidden Variables 1998
Sowmya Ramachandran and Raymond J. Mooney, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 139 pages. Also appears as Technical Report AI 98-265, Artificial Intelligence Lab, University of Texas at Austin.
Towards a formalization of the spatial semantic hierarchy 1998
Emilio Remolina and Benjamin Kuipers, In Fourth Symposium on Logical Formalizations of Commonsense Reasoning (Common Sense 98), London, England, January 1998.
Towards Collaborative and Adversarial Learning: A Case Study in Robotic Soccer 1998
Peter Stone and Manuela Veloso, International Journal of Human-Computer Studies, Vol. 48, 1 (1998), pp. 83-104.
Using Decision Tree Confidence Factors for Multiagent Control 1998
Peter Stone and Manuela Veloso, In RoboCup-97: Robot Soccer World Cup I, Hiroaki Kitano (Eds.), Vol. 1395, pp. 99-111, Berlin 1998. Springer Verlag.
Using Multi-Strategy Learning to Improve Planning Efficiency and Quality 1998
Tara A. Estlin, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
An Inductive Logic Programming Method for Corpus-based Parser Construction 1997
John M. Zelle and Raymond J. Mooney, unpublished. Unpublished Technical Note.
Applying ILP-based Techniques to Natural Language Information Extraction: An Experiment in Relational Learning 1997
Mary Elaine Califf and Raymond J. Mooney, In Workshop Notes of the IJCAI-97 Workshop on Frontiers of Inductive Logic Programming, pp. 7--11, Nagoya, Japan, August 1997.
Automated Modeling of Complex Systems to Answer Prediction Questions 1997
J. Rickel and Bruce Porter, PhD Thesis, Department of Computer Sciences, University of Texas.
Building Concept Representations from Reusable Components. 1997
Peter Clark and Bruce Porter, In AAAI'97, pp. 369--376 1997. CA: AAAI Press. (Best Paper Award).
Causal Theories of Action and Change 1997
Norman McCain and Hudson Turner, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 460-465 1997.
Causality in Commonsense Reasoning about Actions 1997
Norman McCain, PhD Thesis, Computer Sciences Department, The University of Texas at Austin.
Convergence-Zone Episodic Memory: Analysis And Simulations 1997
Mark Moll and Risto Miikkulainen, Neural Networks, Vol. 10 (1997), pp. 1017--1036.
Culling And Teaching In Neuro-Evolution 1997
Paul McQuesten and Risto Miikkulainen, In Proceedings of the Seventh International Conference on Genetic Algorithms (ICGA-97, East Lansing, MI), Thomas B{"a}ck (Eds.), pp. 760-767 1997. San Francisco, CA: Morgan Kaufmann.
Developing and Empirically Evaluating Robust Explanation Generators: The KNIGHT Experiments 1997
James C. Lester, Bruce Porter, Computational Linguistics Journal, Vol. 23, 1 (1997), pp. 65--101.
Dual Reinforcement Q-Routing: An On-Line Adaptive Routing Algorithm 1997
Shailesh Kumar and Risto Miikkulainen, Smart Engineering Systems: Neural Networks, Fuzzy Logic, Data Mining, and Evolutionary ProgrammingC. H. Dagli, M. Akay, O. Ersoy, B. R. Fernandez and A. Smith (Eds.), Vol. 7 (1997).
Dyslexic and Category-Specific Aphasic Impairments in a Self-Organizing Feature Map Model of the Lexicon 1997
Risto Miikkulainen, Brain and Language (1997), pp. 334-366.
Forming Neural Networks Through Efficient And Adaptive Coevolution 1997
David E. Moriarty and Risto Miikkulainen, Evolutionary Computation, Vol. 5 (1997), pp. 373--399.
Incremental Evolution Of Complex General Behavior 1997
Faustino Gomez and Risto Miikkulainen, Adaptive Behavior, 5 (1997), pp. 317-342.
Integrating Abduction and Induction in Machine Learning 1997
Raymond J. Mooney, In Working Notes of the IJCAI-97 Workshop on Abduction and Induction in AI, pp. 37--42, Nagoya, Japan, August 1997.
Interactive, Repair-Based Planning and Scheduling for Shuttle Payload Operations 1997
Gregg Rabideau, Steve Chien, Peter Stone, Jason Willis, Curt Eggemeyer, and Tobias Mann, In Proceedings of the 1997 IEEE Aerospace Conference, pp. 325-341, Aspen, CO, February 1997.
Iterative Refinement of Knowledge Bases with Consistency Guarantees 1997
Stephen F. Correl and Bruce W. Porter , No other information
Learning Parse and Translation Decisions From Examples With Rich Context 1997
Ulf Hermjakob and Raymond J. Mooney, In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics (ACL'97/EACL'97), pp. 482-489, July 1997.
Learning Parse and Translation Decisions From Examples With Rich Context 1997
Ulf Hermjakob, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 175 pages. Technical Report UT-AI97-261.
Learning to Improve both Efficiency and Quality of Planning 1997
Tara A. Estlin and Raymond J. Mooney, In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97), pp. 1227-1232, Nagoya, Japan 1997.
Learning to Parse Natural Language Database Queries into Logical Form 1997
Cynthia A. Thompson, Raymond J. Mooney, and Lappoon R. Tang, In Proceedings of the ML-97 Workshop on Automata Induction, Grammatical Inference, and Language Acquisition, Nashville, TN, July 1997.
Natural Language Processing With Subsymbolic Neural Networks 1997
Risto Miikkulainen, In Neural Network Perspectives on Cognition and Adaptive Robotics, Antony Browne (Eds.), pp. 120-139, Bristol, UK; Philadelphia, PA 1997. Institute of Physics Publishing.
On the Logic of Causal Explanation 1997
Vladimir Lifschitz, Artificial Intelligence, Vol. 96 (1997), pp. 451-465.
Parameter Revision Techniques for Bayesian Networks with Hidden Variables: An Experimental Comparison 1997
Sowmya Ramachandran and Raymond J. Mooney, unpublished. Unpublished Technical Note.
Reflections in Silicon: Artificial and Natural Neural Networks 1997
Rick W. Tanney, Masters Thesis, Department of Philosophy, the University of Texas at Austin.
Relational Learning of Pattern-Match Rules for Information Extraction 1997
Mary Elaine Califf and Raymond J. Mooney, In Proceedings of the ACL Workshop on Natural Language Learning, pp. 9-15, Madrid, Spain, July 1997.
Relational Learning Techniques for Natural Language Information Extraction 1997
Mary Elaine Califf, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Representing Action: Indeterminacy and Ramifications 1997
Enrico Giunchiglia, G. Neelakantan Kartha and Vladimir Lifschitz, Artificial Intelligence, Vol. 95 (1997), pp. 409-443.
Representing Actions in Logic Programs and Default Theories: a Situation Calculus Approach 1997
Hudson Turner, Journal of Logic Programming, Vol. 31 (1997), pp. 245-298.
Self-Organization And Segmentation With Laterally Connected Spiking Neurons 1997
Yoonsuck Choe and Risto Miikkulainen, In Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97), pp. 1120-1125, Nagoya, Japan 1997. San Francisco: Kaufmann.
Self-Organization, Plasticity, and Low-Level Visual Phenomena in a Laterally Connected Map Model of the Primary Visual Cortex 1997
Risto Miikkulainen, James A. Bednar, Yoonsuck Choe, and Joseph Sirosh, In Perceptual Learning, R. L. Goldstone and P. G. Schyns and D. L. Medin (Eds.), pp. 257-308 1997.
Semantic Lexicon Acquisition for Learning Parsers 1997
Cynthia A. Thompson and Raymond J. Mooney, unpublished. Submitted for review.
Software Reuse by Specialization of Generic Procedures through Views 1997
Gordon S. Novak Jr., IEEE Trans. on Software Engineering, Vol. 23, 7 (1997), pp. 1-17.
Symbiotic Evolution Of Neural Networks In Sequential Decision Tasks 1997
David E. Moriarty, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 117. Technical Report UT-AI97-257.
The RoboCup Synthetic Agent Challenge 97 1997
Hiroaki Kitano, Milind Tambe, Peter Stone, Manuela Veloso, Silvia Coradeschi, Eiichi Osawa, Hitoshi Matsubara, Itsuki Noda, and Minoru Asada, In Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, pp. 24-29, San Francisco, CA 1997. Morgan Kaufmann.
Tilt Aftereffects in a Self-Organizing Model of the Primary Visual Cortex 1997
James A. Bednar, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI97-259.
Two Components of an Action Language 1997
Vladimir Lifschitz, Annals of Mathematics and Artificial Intelligence, Vol. 21 (1997), pp. 305-320.
Update by Means of Inference Rules 1997
Teodor Przymusinski and Hudson Turner, Journal of Logic Programming, Vol. 30, 2 (1997), pp. 125-143.
Using Access Paths to Guide Inference with Conceptual Graphs 1997
Peter Clark and Bruce Porter, In Proc Int Conf on Conceptual Structures - ICCS'97 (Lecture Notes in AI), D. lukose, H. Delugach, M. Keeler, L. Searle, J. Sowa (Eds.), Vol. 1257, pp. 521--535, Berlin, Germany 1997. Springer.
Visual Schemas In Neural Networks For Object Recognition And Scene Analysis 1997
Wee Kheng Leow, Risto Miikkulainen, Connection ScienceMichael A. Arbib (Eds.) (1997), pp. 1029-1031. MIT Press.
A Compositional Approach to Representing Planning Operators 1996
Peter Clark, Bruce Porter, and Don Batory , Technical Report AI06-331, University of Texas at Austin.
A Computational Model of Complex Concept Composition 1996
C. Andersen , Masters Thesis, Department of Computer Science, University of Texas at Austin.
A hierarchy of qualitative representations for space 1996
Benjamin Kuipers, In Working Papers of the Tenth International Workshop on Qualitative Reasoning About Physical Systems, Menlo Park, CA 1996. AAAI Press.
A Neural Network Model of Topographic Reorganization Following Cortical Lesions 1996
Joseph Sirosh and Risto Miikkulainen, In Computational Medicine, Public Health and Biotechnology: Building a Man in the Machine - Proceedings of the First World Congress Part II, M. Witten (Eds.), pp. 887-901, 1996. Teaneck, NJ: ...
A Novel Application of Theory Refinement to Student Modeling 1996
Paul Baffes and Raymond J. Mooney, In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pp. 403-408, Portland, OR, August 1996.
Advantages of Decision Lists and Implicit Negative in Inductive Logic Programming 1996
Mary Elaine Califf and Raymond J. Mooney, Technical Report, Artificial Intelligence Lab, University of Texas at Austin.
Beating a Defender in Robotic Soccer: Memory-Based Learning of a Continuous Function 1996
Peter Stone and Manuela Veloso, In Advances in Neural Information Processing Systems 8, David S. Touretzky and Michael C. Mozer and Michael E. Hasselmo (Eds.), pp. 896-902, Cambridge, MA 1996. MIT Press.
Building a Dedicated Robotic Soccer System 1996
Sorin Achim, Peter Stone, and Manuela Veloso, In Proceedings of the IROS-96 Workshop on RoboCup, pp. 41-48, Osaka, Japan, November 1996.
Combining Symbolic and Connectionist Learning Methods to Refine Certainty-Factor Rule-Bases 1996
J. Jeffrey Mahoney, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 113 pages.
Comparative Experiments on Disambiguating Word Senses: An Illustration of the Role of Bias in Machine Learning 1996
Raymond J. Mooney, In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-96), pp. 82-91, Philadelphia, PA 1996.
Comparative Results on Using Inductive Logic Programming for Corpus-based Parser Construction 1996
John M. Zelle and Raymond J. Mooney, In Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, Stefan Wermter and Ellen Riloff and Gabriela Scheler (Eds.), pp. 355-369, Berlin 1996. Spri...
Corpus-Based Lexical Acquisition For Semantic Parsing 1996
Cynthia Thompson, unpublished. Ph.D. proposal.
Efficient Reinforcement Learning Through Symbiotic Evolution 1996
David E. Moriarty and Risto Miikkulainen, Machine LearningLeslie Pack Kaelbling (Eds.), AI94-224 (1996), pp. 11-32.
Evolving Obstacle Avoidance Behavior In A Robot Arm 1996
David E. Moriarty and Risto Miikkulainen, In From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, Pattie Maes and Maja J. Mataric and Jean-Arcady Meyer and Jordan Pollack an...
Foundations of Logic Programming 1996
Vladimir Lifschitz , In Principles of Knowledge Representation, Brewka, Gerhard (Eds.), pp. 69-128 1996. CSLI Publications.
Hybrid Learning of Search Control for Partial-Order Planning 1996
Tara A. Estlin and Raymond J. Mooney, In New Directions in AI Planning, Malik Ghallab and Alfredo Milani (Eds.), pp. 129-140, Amsterdam 1996. IOS Press.
Inductive Logic Programming for Natural Language Processing 1996
Raymond J. Mooney, In Inductive Logic Programming: Selected papers from the 6th International Workshop, Stephen Muggleton (Eds.), pp. 3-22, Berlin 1996. Springer Verlag.
Integrating EBL and ILP to Acquire Control Rules for Planning 1996
Tara A. Estlin and Raymond J. Mooney, Proceedings of the Third International Workshop on Multi-Strategy Learning (MSL-96) (1996), pp. 271--279.
Integrating Explanation-Based and Inductive Learning Techniques to Acquire Search-Control for Planning 1996
Tara A. Estlin, Technical Report AI96-250, Department of Computer Sciences, University of Texas.
Introduction: The Emerging Understanding of Lateral Interactions in the Cortex 1996
Risto Miikkulainen and Joseph Sirosh, In Lateral Interactions in the Cortex: Structure and Function, Sirosh, J., Miikkulainen, R., and Choe, Y. (Eds.) 1996. Electronic book, http://nn.cs.utexas.edu/web-pubs/htmlbook96.
Lateral Interactions In The Cortex: Structure And Function 1996
Joseph Sirosh, Risto Miikkulainen, and Yoonsuck Choe (editors), Electronic book, ISBN 0-9647060-0-8, http://nn.cs.utexas.edu/web-pubs/htmlbook96/. Austin, TX: The UTCS Neural Networks Research Group
Laterally Interconnected Self-Organizing Maps In Hand-Written Digit Recognition 1996
Yoonsuck Choe, Joseph Sirosh, and Risto Miikkulainen, In Advances in Neural Information Processing Systems 8, David S. Touretzky and Michael C. Mozer and Michael E. Hasselmo (Eds.), pp. 736-742 1996. Cambridge, MA: MIT Press.
Learning the Past Tense of English Verbs Using Inductive Logic Programming 1996
Raymond J. Mooney and Mary Elaine Califf, In Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing, {S. Wermter, E. Riloff} and G. Scheler (Eds.), pp. 370-384, Berlin 1996. Springer.
Learning to Parse Database Queries using Inductive Logic Programming 1996
John M. Zelle and Raymond J. Mooney, In AAAI/IAAI, pp. 1050-1055, Portland, OR, August 1996. AAAI Press/MIT Press.
Lexical Acquisition: A Novel Machine Learning Problem 1996
Cynthia A. Thompson and Raymond J. Mooney, Technical Report, Artificial Intelligence Lab, University of Texas at Austin.
Multi-Strategy Learning of Search Control for Partial-Order Planning 1996
Tara A. Estlin and Raymond J. Mooney, In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pp. 843-848, Portland, OR, August 1996.
On-Line Adaptation Of A Signal Predistorter Through Dual Reinforcement Learning 1996
Patrick Goetz, Shailesh Kumar and Risto Miikkulainen, In Machine Learning: Proceedings of the 13th Annual Conference (Bari, Italy), Lorenza Saitta (Eds.), pp. 175-181 1996. San Francisco, CA: Morgan Kaufmann.
Predictive Memory for an Inaccessible Environment 1996
Mike Bowling, Peter Stone, and Manuela Veloso, In Proceedings of the IROS-96 Workshop on RoboCup, pp. 28-34, Osaka, Japan, November 1996.
Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes 1996
Siddarth Subramanian and Raymond J. Mooney, In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), pp. 965-970, Portland, OR, August 1996.
Refinement-Based Student Modeling and Automated Bug Library Construction 1996
Paul Baffes and Raymond Mooney, Journal of Artificial Intelligence in Education, Vol. 7, 1 (1996), pp. 75-116.
Revising Bayesian Network Parameters Using Backpropagation 1996
Sowmya Ramachandran and Raymond J. Mooney, In Proceedings of the International Conference on Neural Networks (ICNN-96), Special Session on Knowledge-Based Artificial Neural Networks, pp. 82--87, Washington DC, June 1996.
Self-Organization and Functional Role of Lateral Connections and Multisize Receptive Fields in the Primary Visual Cortex 1996
Joseph Sirosh and Risto Miikkulainen, Neural Processing Letters, Vol. 3 (1996), pp. 39-48.
Self-Organization of Orientation Maps, Lateral Connections, and Dynamic Receptive Fields in the Primary Visual Cortex 1996
Joseph Sirosh, Risto Miikkulainen and James A. Bednar, In {P}roceedings of the {I}nternational {C}onference {on} {A}rtificial {N}eural {N}etworks, Joseph Sirosh and Risto Miikkulainen and Yoonsuck Choe (Eds.), pp. 1147-1152, Berlin 1996. Springer...
Spatial Semantic Hierarchy for a Physical Mobile Robot 1996
Wan Yik Lee, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Splitting a Default Theory 1996
Hudson Turner, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 645-651 1996.
Subsymbolic Case-Role Analysis Of Sentences With Embedded Clauses 1996
Risto Miikkulainen, Cognitive Science, Vol. 20 (1996), pp. 47-73.
Topographic Receptive Fields and Patterned Lateral Interaction in a Self-Organizing Model of the Primary Visual Cortex 1996
Joseph Sirosh and Risto Miikkulainen, Neural Computation, Vol. 9 (1996), pp. 577-594.
User-guided Interleaving of Planning and Execution 1996
Peter Stone and Manuela Veloso, In New Directions in AI Planning, M. Ghallab and A. Milani (Eds.), pp. 103-112 1996. IOS Press.
A Causal Theory of Ramifications and Qualifications 1995
Norman McCain and Hudson Turner, In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 1978-1984 1995.
A Comparison of Two Methods Employing Inductive Logic Programming for Corpus-based Parser Constuction 1995
John M. Zelle and Raymond J. Mooney, In Working Notes of the IJCAI-95 Workshop on New Approaches to Learning for Natural Language Processing, pp. 79--86, Montreal, Quebec, Canada, August 1995.
A Guide to Programming Spot, a Mobile Robot of the University of Texas at Austin 1995
Wan Yik Lee, Technical Report AI95-235, Artificial Intelligence Laboratory, The University of Texas at Austin, AI Laboratory.
A Mathematical Investigation of Reasoning about Actions 1995
Neelakantan Kartha , PhD Thesis, University of Texas at Austin. (Available by anonymous ftp from ftp.cs.utexas.edu as /pub/techreports/tr95-17.ps).
A Model Of Visually Guided Plasticity Of The Auditory Spatial Map In The Barn Owl 1995
Andrea Haessly, Joseph Sirosh and Risto Miikkulainen, In Proceedings of the 17th Annual Conference of the Cognitive Science Society, pp. 154-158 1995. Hillsdale, NJ: Erlbaum.
A Preliminary PAC Analysis of Theory Revision 1995
Raymond J. Mooney, In Computational Learning Theory and Natural Learning Systems, Vol. 3, T. Petsche and S. Hanson and Jude W. Shavlik (Eds.), pp. 43-53, Cambridge, MA 1995. MIT Press.
A Self-Organizing Neural Network Model Of The Primary Visual Cortex 1995
Joseph Sirosh, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI95-237.
A Simple Formalization of Actions Using Circumscription 1995
G. Neelakantan Kartha and Vladimir Lifschitz, In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 1970-1975 1995.
Acquisition of a Lexicon from Semantic Representations of Sentences 1995
Cynthia A. Thompson, In Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (ACL-95), pp. 335-337, Cambridge, MA 1995.
Automated Modeling of Complex Systems for Answering Prediction Questions 1995
J. Rickel , PhD Thesis, Department of Computer Sciences, University of Texas at Austin.
Automated Refinement of First-Order Horn-Clause Domain Theories 1995
Bradley L. Richards and Raymond J. Mooney, Machine Learning, Vol. 19, 2 (1995), pp. 95-131.
Conversion of Units of Measurement 1995
Gordon S. Novak Jr., IEEE Trans. on Software Engineering, Vol. 21, 8 (1995), pp. 651-661.
Creation of Views for Reuse of Software with Different Data Representations 1995
Gordon S. Novak Jr., IEEE Trans. on Software Engineering, Vol. 21, 12 (1995), pp. 993-1005.
Dependent Fluents 1995
Enrico Giunchiglia and Vladimir Lifschitz, In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), pp. 1964-1969 1995.
Diagrams for Solving Physical Problems 1995
Gordon Novak, In Diagrammatic Reasoning: Cognitive and Computational Perspectives, Glasgow, Janice and Narayanan, N. Hari and Chandrasekaran, B. (Eds.), pp. 753-774, Boston, MA 1995. AAAI Press / MIT Press.
Discovering Complex Othello Strategies Through Evolutionary Neural Networks 1995
David E. Moriarty and Risto Miikkulainen, Connection Science, Vol. 7 (1995), pp. 195--209.
ECWA Made Easy 1995
Vladimir Lifschitz, Annals of Mathematics and Artificial Intelligence, Vol. 14 (1995), pp. 269-274.
Encouraging Experimental Results on Learning CNF 1995
Raymond J. Mooney, Machine Learning, Vol. 19, 1 (1995), pp. 79-92.
FLECS: Planning with a Flexible Commitment Strategy 1995
Manuela Veloso and Peter Stone, Journal of Artificial Intelligence Research, Vol. 3 (1995), pp. 25-52.
From Disjunctive Programs to Abduction 1995
Vladimir Lifschitz and Hudson Turner, In Non-Monotonic Extensions of Logic Programming (Lecture Notes in Artificial Intelligence 927), Dix, J{"u}rgen and Pereira, Luis and Przymusinski, Teodor (Eds.), pp. 23-42 1995. Springer.
High-Speed Navigation with Approximate Maps 1995
Richard Froom, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Inducing Logic Programs without Explicit Negative Examples 1995
John M. Zelle, Cynthia A. Thompson, Mary Elaine Califf, and Raymond J. Mooney, In Proceedings of the Fifth International Workshop on Inductive Logic Programming (ILP-95), pp. 403-416, Leuven, Belgium 1995.
Induction of First-Order Decision Lists: Results on Learning the Past Tense of English Verbs 1995
Raymond J. Mooney and Mary Elaine Califf, Journal of Artificial Intelligence Research, Vol. 3 (1995), pp. 1-24.
Laterally Interconnected Self-Organizing Feature Map In Handwritten Digit Recognition 1995
Yoonsuck Choe, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 65. Technical Report AI95-236.
Learning Sequential Decision Tasks 1995
David E. Moriarty and Risto Miikkulainen, Technical Report AI95-229, Department of Computer Sciences, The University of Texas at Austin.
Loop Checking and the Well-founded Semantics 1995
Vladimir Lifschitz, Norman McCain, Teodor C. Przymusinski and Robert F. Staerk, In Logic Programming and Non-monotonic Reasoning: Proceedings of the Third Int'l Conf., pp. 127-142 1995.
Map Learning with Uninterpreted Sensors and Effectors 1995
David M. Pierce, Artificial Intelligence (1995), pp. 169-227. 169-227.
Modeling Cortical Plasticity Based On Adapting Lateral Interaction 1995
Joseph Sirosh and Risto Miikkulainen, In The Neurobiology of Computation: {T}he Proceedings of the Third Annual Computation and Neural Systems Conference, James M. Bower (Eds.), pp. 305-310 1995.
Multiple-Fault Diagnosis Using General Qualitative Models with Fault Modes 1995
Siddarth Subramanian and Raymond J. Mooney, In Working Notes of the IJCAI-95 Workshop on Engneering Problems for Qualitative Reasoning, Monreal, Quebec, August 1995.
Nested Abnormality Theories 1995
Vladimir Lifschitz, Artificial Intelligence, Vol. 74 (1995), pp. 351-365.
Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex 1995
Joseph Sirosh and Risto Miikkulainen, In Advances in Neural Information Processing Systems 7, Gerald Tesauro and David S. Touretzky and Todd K. Leen (Eds.), pp. 109-116 1995. Cambridge, MA: MIT Press.
Programming Spot in Lisp with SpotLisp Package 1995
Wan Yik Lee, Technical Report AI95-240, Artificial Intelligence Laboratory, The University of Texas at Austin.
Qualitative Multiple-Fault Diagnosis of Continuous Dynamic Systems Using Behavioral Modes 1995
Siddarth Subramanian, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 128 pages. Also appears as Technical Report AI 95-239.
Qualitative reasoning about dynamic change in the spatial properties of a physical system 1995
Raman Rajagopalan, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. Available as TR AI95-241.
Refinement of Bayesian Networks by Combining Connectionist and Symbolic Techniques 1995
Sowmya Ramachandran, Unpublished Ph.D. Thesis Proposal.
Robust Natural Language Generation from Large-Scale Knowledge Bases 1995
Charles B. Callaway and James Lester, In Proceedings of the Fourth Bar-Ilan Symposium on the Foundations of AI 1995.
SARDNET: A Self-Organizing Feature Map For Sequences 1995
Daniel L. James and Risto Miikkulainen, In Advances in Neural Information Processing Systems 7 (NIPS'94), G. Tesauro, D. S. Touretzky, and T. K. Leen (Eds.), pp. 577--584, Denver, CO 1995. Cambridge, MA: MIT Press.
Script-Based Inference And Memory Retrieval In Subsymbolic Story Processing 1995
Risto Miikkulainen, Applied Intelligence (1995), pp. 137-163.
SLDNF, Constructive Negation and Grounding 1995
Vladimir Lifschitz, In Proceedings ICLP-95, pp. 581-595 1995.
Slow visual search in a fast-changing world 1995
William S. Gribble, In Proceedings of the 1995 IEEE Symposium on Computer Vision (ISCV-95) 1995.
The Logic of Common Sense 1995
Vladimir Lifschitz, ACM Computing Surveys, Vol. 27 (1995), pp. 343-345.
Using Inductive Logic Programming to Automate the Construction of Natural Language Parsers 1995
John M. Zelle, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Using Testing to Iteratively Improve Training 1995
Peter Stone and Manuela Veloso, In Working Notes of the AAAI 1995 Fall Symposium on Active Learning, pp. 110-111, Boston, MA, November 1995.
Visual Schemas In Object Recognition And Scene Analysis 1995
Risto Miikkulainen and Wee Kheng Leow, In The Handbook of Brain Theory and Neural Networks, M. A. Arbib (Eds.), pp. 1029--1031, Cambridge, MA 1995. MIT Press.
Visualizing High-Dimensional Structure with the Incremental Grid Growing Network 1995
Justine Blackmore, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI95-238.
Visualizing High-Dimensional Structure With The Incremental Grid Growing Neural Network 1995
Justine Blackmore and Risto Miikkulainen, In Machine Learning: Proceedings of the 12th Annual Conference, Armand Prieditis and Stuart Russell (Eds.), pp. 55-63, Austin, TX 1995. San Francisco, CA: Morgan Kaufmann. 55-63. Technical Repo...
A Connectionist Corpus-Based Approach to the Building of Word Representations 1994
Rupert L. Tang, Technical Report HR-94-01, Department of Computer Science, The University of Texas at Austin.
A Multistrategy Approach to Theory Refinement 1994
Raymond J. Mooney and Dirk Ourston, In Machine Learning: A Multistrategy Approach, Vol. IV, Ryszard S. Michalski and G. Teccuci (Eds.), pp. 141-164, San Mateo, CA 1994. Morgan Kaufmann.
Actions with Indirect Effects (preliminary report) 1994
G. Neelakantan Kartha and Vladimir Lifschitz, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), pp. 341-350 1994.
Analysis and Empirical Studies of Derivational Analogy 1994
B. Blumenthal and Bruce Porter, Artificial Intelligence Journal, Vol. 67, 2 (1994), pp. 287--328.
Autoepistemic Logic and Introspective Circumscription 1994
Michael Gelfond, Vladimir Lifschitz, Halina Przymusinska and Grigori Schwarz, In Theoretical Aspects of Reasoning about Knowledge: Proceedings Fifth Conf., Fagin, Ronald (Eds.), pp. 197-207 1994.
Automated Modeling for Answering Prediction Questions: Selecting the Time Scale and System Boundary 1994
J. Rickel and Bruce Porter , In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 1191--1198, Cambridge, MA 1994. AAAI/MIT Press.
Automatic Student Modeling and Bug Library Construction using Theory Refinement 1994
Paul T. Baffes, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin.
Circumscription 1994
Vladimir Lifschitz, Handbook of Logic in AI and Logic Programming, Vol. 3 (1994), pp. 298--352. Oxford University Press.
Combining Top-Down And Bottom-Up Techniques In Inductive Logic Programming 1994
John M. Zelle, Raymond J. Mooney, and Joshua B. Konvisser, In Proceedings of the Eleventh International Workshop on Machine Learning (ML-94), pp. 343--351, Rutgers, NJ, July 1994.
Comparing Methods For Refining Certainty Factor Rule-Bases 1994
J. Jeffrey Mahoney and Raymond J. Mooney, In Proceedings of the Eleventh International Workshop on Machine Learning (ML-94), pp. 173--180, Rutgers, NJ, July 1994.
Composing Reusable Software Components through Views 1994
Gordon S. Novak Jr., In Proc. 9th Knowledge-Based Software Engineering Conference (KBSE-94), pp. 39-47, Monterey, CA, September 1994. IEEE Computer Society Press.
Cooperative Self-Organization Of Afferent And Lateral Connections In Cortical Maps 1994
Joseph Sirosh and Risto Miikkulainen, Biological Cybernetics (1994), pp. 66-78.
Evolutionary Neural Networks For Value Ordering In Constraint Satisfaction Problems 1994
David E. Moriarty and Risto Miikkulainen, Technical Report AI94-218, Department of Computer Sciences, The University of Texas at Austin.
Evolving Neural Networks To Focus Minimax Search 1994
David E. Moriarty and Risto Miikkulainen, In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 1371-1377, Seattle, WA 1994. Cambridge, MA: MIT Press.
Extracting Viewpoints from Knowledge Bases 1994
Liane Acker and Bruce Porter , In Proceedings of the 12th National Conference on Artificial Intelligence, pp. 547-552 1994.
Generating Programs from Connections of Physical Models 1994
Gordon S. Novak Jr., In Proc. 10th Conference on Artificial Intelligence for Applications (CAIA-94), pp. 224-230, San Antonio, TX, March 1994.
Grounding Robotic Control With Genetic Neural Networks 1994
Diane Law and Risto Miikkulainen, Technical Report AI94-223, Department of Computer Sciences, The University of Texas at Austin.
Inducing Deterministic Prolog Parsers From Treebanks: A Machine Learning Approach 1994
John M. Zelle and Raymond J. Mooney, Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94) (1994), pp. 748--753.
Inductive Learning For Abductive Diagnosis 1994
Cynthia A. Thompson and Raymond J. Mooney, In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 664-669, Seattle, WA, August 1994.
Integrated Connectionist Models: Building AI Systems on Subsymbolic Foundations 1994
Risto Miikkulainen, Artificial Intelligence and Neural Networks: Steps Toward Principled IntegrationHonavar, V., and Uhr, L. (Eds.) (1994), pp. 483--508.
Integrating ILP and EBL 1994
Raymond J. Mooney and John M. Zelle, Sigart Bulletin (special issue on Inductive Logic Programmming), Vol. 5, 1 (1994), pp. 12-21.
Language Independence and Language Tolerance in Logic Programs 1994
Norman McCain and Hudson Turner, In Proceedings Eleventh Int'l Conf. on Logic Programming, Van Hentenryck, Pascal (Eds.), pp. 38-57 1994.
Learning Qualitative Models for Systems with Multiple Operating Regions 1994
Sowmya Ramachandran, Raymond J. Mooney, and Benjamin J. Kuipers, In Proceedings of the Eighth International Workshop on Qualitative Reasoning about Physical Systems, Nara, Japan 1994.
Learning to explore and build maps 1994
D. Pierce and Benjamin Kuipers, In Proceedings of the National Conference on Artificial Intelligence (AAAI-94) 1994. AAAI/MIT Press.
Learning to Solve Complex Planning Problems: Finding Useful Auxiliary Problems 1994
Peter Stone and Manuela Veloso, In Technical Report of the AAAI 1994 Fall Symposium on Planning and Learning: On to Real Applications, pp. 137-141, New Orleans, LA, November 1994.
Lexical Disambiguation Based on Distributed Representations of Context Frequency 1994
Marshall R. Mayberry III and Risto Miikkulainen, In Proceedings of the 16th Annual Conference of the Cognitive Science Society, Ashwin Ram and Kurt Eiselt (Eds.), pp. 601-606 1994. Hillsdale, NJ: Erlbaum.
Minimal Belief and Negation as Failure 1994
Vladimir Lifschitz, Artificial IntelligenceGabbay, D.M. and Hogger, C.J. and Robinson, J.A. (Eds.), Vol. 70 (1994), pp. 53--72. Oxford University Press.
Modifying Network Architectures For Certainty-Factor Rule-Base Revision 1994
J. Jeffrey Mahoney and Raymond J. Mooney, In Proceedings of the International Symposium on Integrating Knowledge and Neural Heuristics (ISIKNH-94), pp. 75--85, Pensacola, FL, May 1994.
Multiple-Fault Diagnosis Using General Qualitative Models with Fault Modes 1994
Siddarth Subramanian and Raymond J. Mooney, In Working Papers of the Fifth International Workshop on Principles of Diagnosis, pp. 321-325, New Paltz, NY, October 1994.
Parsing Embedded Clauses with Distributed Neural Networks 1994
Risto Miikkulainen and Dennis Bijwaard, In Proceedings of the Twelfth National Conference on Artificial Intelligence, pp. 858-864, January 1994.
Parsing Embedded Clauses with Distributed Neural Networks 1994
Risto Miikkulainen and Dennis Bijwaard, In Proceedings of the Twelfth National Conference on Artificial Intelligence, pp. 858-864, January 1994.
Priming, Perceptual Reversal, And Circular Reaction In A Neural Network Model Of Schema-Based Vision 1994
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the 16th Annual Conference of the Cognitive Science Society, Ashwin Ram and Kurt Eiselt (Eds.), pp. 560-565 1994. Hillsdale, NJ: Erlbaum.
Representing And Learning Visual Schemas In Neural Networks For Scene Analysis 1994
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the Workshop on Neural Architectures and Distributed {AI}: {F}rom Schema Assemblages to Neural Networks, pp. 35-40, Los Angeles 1994. Center for Neural Engineering, Universit...
Searle, Subsymbolic Functionalism And Synthetic Intelligence 1994
Diane Law, Technical Report, Department of Computer Sciences, The University of Texas at Austin. Technical Report AI94-222.
Self-Organizing Feature Maps With Lateral Connections: Modeling Ocular Dominance 1994
Joseph Sirosh and Risto Miikkulainen, In Proceedings of the 1993 Connectionist Models Summer School, M. C. Mozer and P. Smolensky and D. S. Touretzky and J. L. Elman and A. S. Weigend (Eds.), pp. 31-38 1994.
Short Algernon Reference Manual (for Algernon version 1.3.0) 1994
Benjamin J. Kuipers and J. M. Crawford, unpublished. Unpublished manuscript.
Signed Logic Programs 1994
Hudson Turner, In Proceedings ILPS-94, pp. 61-75 1994.
Splitting a Logic Program 1994
Vladimir Lifschitz and Hudson Turner, In Proceedings of International Conference on Logic Programming (ICLP), Van Hentenryck, Pascal (Eds.), pp. 23-37 1994.
The Capacity Of Convergence-Zone Episodic Memory 1994
Mark Moll, Risto Miikkulainen, Jonathan Abbey, In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 68-73, Seattle, WA 1994. Cambridge, MA: MIT Press.
The composition and validation of heterogeneous control laws 1994
Benjamin J. Kuipers and K. Astrom, Automatica, Vol. 30, 2 (1994), pp. 233--249.
The need for different domain-independent heuristics 1994
Peter Stone, Manuela Veloso, and Jim Blythe, In Proceedings of the Second International Conference on AI Planning Systems, pp. 164-169, June 1994.
Theory Refinement Combining Analytical and Empirical Methods 1994
Dirk Ourston and Raymond J. Mooney, Artificial Intelligence (1994), pp. 311-344.
Verb Inflections in German Child Language: A Connectionist Account 1994
Gert Westermann and Risto Miikkulainen, In Proceedings of the 16th Annual Conference of the Cognitive Science Society, Ashwin Ram and Kurt Eiselt (Eds.), pp. 928-933 1994. Hillsdale, NJ: Erlbaum.
VISOR: Learning Visual Schemas In Neural Networks For Object Recognition And Scene Analysis 1994
Wee Kheng Leow, PhD Thesis, Department of Computer Sciences, The University of Texas at Austin. 198 pages. Technical Report AI-94-219.
VISOR: Schema-Based Scene Analysis With Structured Neural Networks 1994
Wee Kheng Leow and Risto Miikkulainen, Neural Processing Letters, Vol. 1 (1994), pp. 18--23.
A Monotonicity Theorem for Extended Logic Programs 1993
Hudson Turner, In Proceedings Tenth Int'l Conf. on Logic Programming, pp. 567-585 1993.
Algernon for Expert Systems 1993
Benjamin Kuipers, Unpublished manuscript
Automated modeling of physical systems in the presence of incomplete knowledge 1993
Adam Farquhar, PhD Thesis, University of Texas at Austin, Artificial Intelligence Laboratory, Department of Computer Sciences.
Combining Connectionist and Symbolic Learning to Refine Certainty-Factor Rule-Bases 1993
J. Jeffrey Mahoney and Raymond J. Mooney, Connection Science (1993), pp. 339-364.
Combining FOIL and EBG to Speed-Up Logic Programs 1993
John M. Zelle and Raymond J. Mooney, In Proceedings of the 13th International Joint Conference on Artificial Intelligence, pp. 1106-1111 1993. San Francisco, CA: Morgan Kaufmann.
Diagrams and Text as Computer Input 1993
Gordon Novak and William Bulko, Journal of Visual Languages and Computing, Vol. 4, 4 (1993), pp. 161-175.
Extended Logic Programs as Autoepistemic Theories 1993
Vladimir Lifschitz and Grigori Schwarz, In Logic Programming and Non-monotonic Reasoning: Proceedings of the Second Int'l Workshop, Pereira, Luis Moniz and Nerode, Anil (Eds.), pp. 101-114 1993.
Extending Theory Refinement to M-of-N Rules 1993
Paul T. Baffes and Raymond J. Mooney, Informatica, Vol. 17 (1993), pp. 387-397.
How Lateral Interaction Develops In A Self-Organizing Feature Map 1993
Joseph Sirosh and Risto Miikkulainen, In Proceedings of the IEEE International Conference on Neural Networks (San Francisco, CA), pp. 1360-1365 1993. Piscataway, NJ: IEEE.
Incremental Grid Growing: Encoding High-Dimensional Structure Into A Two-Dimensional Feature Map 1993
Justine Blackmore and Risto Miikkulainen, In Proceedings of the IEEE International Conference on Neural Networks (San Francisco, CA), pp. 450-455 1993. Piscataway, NJ: IEEE.
Induction Over the Unexplained: Using Overly-General Domain Theories to Aid Concept Learning 1993
Raymond J. Mooney, Machine Learning, Vol. 10 (1993), pp. 79-110.
Inductive Learning For Abductive Diagnosis 1993
Cynthia A. Thompson, Masters Thesis, Department of Computer Sciences, The University of Texas at Austin. 53 pages.
Integrating Theory and Data in Category Learning 1993
Raymond J. Mooney, In Categorization by Humans and Machines, G. V. Nakamura and D. L. Medin and R. Taraban (Eds.), pp. 189-218 1993.
Learning Search-Control Heuristics for Logic Programs: Applications to Speedup Learning and Language Acquisition 1993
John M. Zelle, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Learning Semantic Grammars With Constructive Inductive Logic Programming 1993
John M. Zelle and Raymond J. Mooney, In Proceedings of the 11th National Conference on Artificial Intelligence, pp. 817-822 1993. Menlo Park, CA: AAAI Press.
Learning to Model Students: Using Theory Refinement to Detect Misconceptions 1993
Paul T. Baffes, unpublished. Ph.D. proposal, Department of Computer Sciences, University of Texas at Austin.
Multi-Level Neural Network Language Translator 1993
James A. Bednar, Technical Report HR-93-01, Department of Computer Sciences, The University of Texas at Austin.
Representing Action and Change by Logic Programs 1993
Michael Gelfond and Vladimir Lifschitz, Journal of Logic Programming, Vol. 17 (1993), pp. 301-322.
Representing Visual Schemas in Neural Networks for Scene Analysis 1993
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the IEEE Conference on Neural Networks (ICNN-93), pp. 1612-1617, San Francisco, CA 1993. Piscataway, NJ: IEEE.
Restricted Monotonicity 1993
Vladimir Lifschitz, In Proceedings of National Conference on Artificial Intelligence (AAAI), pp. 432-437 1993.
Subsymbolic Natural Language Processing: An Integrated Model Of Scripts, Lexicon, And Memory 1993
Risto Miikkulainen, , MIT Press, Cambridge, MA 1993. MIT Press.
Symbolic Revision of Theories With M-of-N Rules 1993
Paul T. Baffes and Raymond J. Mooney, In Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence (IJCAI-93), pp. 1135-1140, Chambery, France, August 1993.
The semantic hierarchy in robot learning 1993
Benjamin Kuipers, R. Froom, W.-Y. Lee and D. Pierce, Robot LearningJ. Connell and S. Mahadevan (Eds.) (1993).
A First-Order Horn-Clause Abductive System and Its Use in Plan Recognition and Diagnosis 1992
Hwee Tou Ng and Raymond J. Mooney, unpublished. Unpublished Technical Note.
A General Abductive system with application to plan recognition and diagnosis 1992
Hwee Tou Ng, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. 154 pages.
Abductive Plan Recognition and Diagnosis: A Comprehensive Empirical Evaluation 1992
Hwee Tou Ng and Raymond J. Mooney, In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning, pp. 499--508, Cambridge, MA, October 1992.
An Operator-Based Approach to First-Order Theory Revision 1992
Bradley Lance Richards, PhD Thesis, Department of Computer Science, University of Texas at Austin.
Approximate maps for high-speed control of a mobile robot 1992
Richard Froom, In Mobile Robots VII: Proceedings of SPIE -- the International Society for Optical Engineering v. 1831, pp. 15--20, Boston, MA, November 1992.
Automated Debugging of Logic Programs via Theory Revision 1992
Raymond J. Mooney and Bradley L. Richards, In Proceedings of the Second International Workshop on Inductive Logic Programming (ILP-92), Tokyo, Japan 1992.
Automatic Abduction of Qualitative Models 1992
Bradley L. Richards, Ina Kraan, and Benjamin J. Kuipers, In Proceedings of the Fifth International Workshop on Qualitative Reasoning about Physical Systems, pp. 295-301 1992.
Batch versus Incremental Theory Refinement 1992
Raymond J. Mooney, In Proceedings of the 1992 AAAI Spring Symposium on Knowledge Assimilation, Standford, CA, March 1992.
Belief Revision in the Context of Abductive Explanation 1992
Siddarth Subramanian, Technical Report AI92-179, Artificial Intelligence Laboratory, University of Texas.
Combining Symbolic and Neural Learning to Revise Probabilistic Theories 1992
J. Jeffrey Mahoney and Raymond J. Mooney, In Proceedings of the ML92 Workshop on Integrated Learning in Real Domains, Aberdeen, Scotland, July 1992.
Data Rectification Using Recurrent (Elman) Neural Networks 1992
Thomas W. Karjala, David M. Himmelblau and Risto Miikkulainen, In Proceedings of the International Joint Conference on Neural Networks (IJCNN-92), Vol. II, pp. 901--906, Baltimore, MD 1992. Piscataway, NJ: IEEE.
Growing Layers of Perceptrons: Introducing the Extentron Algorithm 1992
Paul T. Baffes and John M. Zelle, In Proceedings of the 1992 International Joint Conference on Neural Networks, pp. 392--397, Baltimore, MD, June 1992.
Learning Relations by Pathfinding 1992
Bradley L. Richards and Raymond J. Mooney, In Proceedings of the Tenth National Conference on Artificial Intelligence (AAAI-92), pp. 50-55, San Jose, CA, July 1992.
Negotiated Interfaces for Software Reuse 1992
Gordon S. Novak Jr., Fredrick N. Hill, Man Lee Wan, and Brian G. Sayrs, IEEE Trans. on Software Engineering, Vol. 18, 7 (1992), pp. 646-653.
Results of an experiment in domain knowledge base construction: a comparison of the Classic and Algernon knowledge representation systems 1992
Raman Rajagopalan, In Working Papers of the AAAI Workshop on Tractable Reasoning (AAAI-92), San Jose, CA 1992.
Schema acquisition from a single example 1992
W. Ahn, W. F. Brewer and Raymond J. Mooney, Journal of Experimental Psychology: Learning, Memory, and Cognition, Vol. 18 (1992), pp. 391-412.
Software Reuse through View Type Clusters 1992
Gordon S. Novak Jr., In Proc. 7th Knowledge-Based Software Engineering Conference (KBSE-92), pp. 70-79, McLean, VA, September 1992. IEEE Computer Society Press.
Speeding-up Logic Programs by Combining EBG and FOIL 1992
John M. Zelle and Raymond J. Mooney, In Proceedings of the 1992 Machine Learning Workshop on Knowledge Compilation and Speedup Learning, Aberdeen, Scotland, July 1992.
Trace Feature Map: A Model Of Episodic Associative Memory 1992
Risto Miikkulainen, Biological Cybernetics, Vol. 66 (1992), pp. 273--282.
Using Theory Revision to Model Students and Acquire Stereotypical Errors 1992
Paul T. Baffes and Raymond J. Mooney, In Proceedings of the Fourteenth Annual Conference of the Cognitive Science Society, pp. 617-622, Bloomington, IN 1992.
A Neural Network For Attentional Spotlight 1991
Wee Kheng Leow and Risto Miikkulainen, In Proceedings of the International Joint Conference on Neural Networks (Singapore), AI91-165, pp. 436-441 1991. Piscataway, NJ: IEEE.
A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations 1991
Benjamin J. Kuipers and Y.-T. Byun, Journal of Robotics and Autonomous Systems, Vol. 8 (1991), pp. 47--63. Reprinted in Walter Van de Velde (ed.), Towards Learning Robots, Bradford/MIT Press, 1993.
Acquiring effective knowledge of environment geometry for minimum-time control of a mobile robot 1991
Richard Froom, In Proceedings of the 1991 IEEE International Symposium on Intelligent Control, pp. 501--506, Arlington, VA, August 1991.
Algernon -- a tractable system for knowledge representation 1991
J. M. Crawford and Benjamin J. Kuipers, SIGART Bulletin, Vol. 2, 3 (1991), pp. 35--44.
ALL: formalizing access-limited reasoning 1991
J. M. Crawford and Benjamin J. Kuipers, In Principles of Semantic Networks, John Sowa (Eds.), pp. 299--330, San Mateo, CA 1991. Morgan Kaufmann.
An Efficient First-Order Horn-Clause Abduction System Based on the ATMS 1991
Hwee Tou Ng and Raymond J. Mooney, In Proceedings of the Ninth National Conference on Artificial Intelligence (AAAI-91), pp. 494-499, Anaheim, CA, July 1991.
Answer Sets in General Nonmonotonic Reasoning (preliminary report) 1991
Vladimir Lifschitz and Thomas Y. C. Woo, In Proceedings of the Third International Conference on Principles of Knowledge Representation and Reasoning, pp. 603--614 1991.
Classical Negation in Logic Programs and Disjunctive Databases 1991
Michael Gelfond and Vladimir Lifschitz, New Generation Computing, Vol. 9 (1991), pp. 365-385.
Constructive Induction in Theory Refinement 1991
Raymond J. Mooney and Dirk Ourston, In Proceedings of the Eighth International Workshop on Machine Learning, pp. 178-182, Evanston, IL, June 1991.
Disjunctive Defaults 1991
Michael Gelfond, Vladimir Lifschitz, Halina Przymusinska and Miroslaw Truszczynski, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), Allen, James and Fikes, Richard and Sandewall, Erik (Eds.), pp. 230-237 1991.
Editorial 1991
Vladimir Lifschitz, Journal of Logic and Computation, Vol. 2 (1991), pp. 671--673.
Evolving Finite State Behavior using Marker-Based Genetic Encoding of Neural Networks 1991
Brad Fullmer, Technical Report HR-91-01, Department of Computer Science, The University of Texas at Austin.
First-Order Theory Revision 1991
Bradley L. Richards and Raymond J. Mooney, In Proceedings of the Eighth International Machine Learning Workshop, pp. pp. 447-451, Evanston, IL, June 1991.
Improving Shared Rules in Multiple Category Domain Theories 1991
Dirk Ourston and Raymond J. Mooney, In Proceedings of the Eighth International Workshop on Machine Learning, pp. 534-538, Evanston, IL, June 1991.
Learning hill-climbing functions as a strategy for generating behaviors in a mobile robot 1991
David M. Pierce and Benjamin J. Kuipers, In From Animals to Animats: Proceedings of the International Conference on Simulation of Adaptive Behavior, J.-A. Meyer and S. W. Wilson (Eds.), pp. 327--336 1991. MIT Press/Bradford Books: Cam...
Learning turn and travel actions with an uninterpreted sensorimotor apparatus 1991
David M. Pierce, In Proceedings of the IEEE International Conference on Robotics and Automation, pp. 246--251, Los Alamitos, CA 1991. IEEE Computer Society Press.
Natural Language Processing With Modular PDP Networks And Distributed Lexicon 1991
Risto Miikkulainen and Michael G. Dyer, Cognitive Science, Vol. 15 (1991), pp. 343-399.
Negation and proof by contradiction in access-limited logic 1991
J. M. Crawford and Benjamin J. Kuipers, In Proceedings of the National Conference on Artificial Intelligence (AAAI-91) 1991. AAAI/MIT Press.
Representation of Models for Expert Problem Solving in Physics 1991
Hyung Joon Kook and Gordon Novak, IEEE Trans. on Knowledge and Data Engineering, Vol. 3, 1 (1991), pp. 48-54.
Rules and Precedents as Complementary Warrants 1991
K. Branting and Bruce Porter, In AAAI-91, pp. 3--9 1991.
Self-Organizing Process Based On Lateral Inhibition And Synaptic Resource Redistribution 1991
Risto Miikkulainen, In Proceedings of the 1991 International Conference on Artificial Neural Networks, Teuvo Kohonen and Kai M{"a}kisara and Olli Simula and Jari Kangas (Eds.), pp. 415-420 1991. Amsterdam: North-H...
Symbolic and Neural Learning Algorithms: An Experimental Comparison 1991
J.W. Shavlik, Raymond J. Mooney and G. Towell, Machine Learning, Vol. 6 (1991), pp. 111-143. Reprinted in {it Readings in Knowledge Acquisition and Learning}, Bruce G. Buchanan and David C. Wilkins (eds.), Morgan Kaufman, San Mateo, CA, 19...
The composition of heterogeneous control laws 1991
Benjamin Kuipers and Karl Astrom, In Proceedings of the American Control Conference, pp. 630--636 1991.
Theory Refinement with Noisy Data 1991
Raymond J. Mooney and Dirk Ourston, Technical Report AI91-153, Artificial Intelligence Laboratory, University of Texas.
Towards a Metatheory of Action 1991
Vladimir Lifschitz, In Proceedings of International Conference on Principles of Knowledge Representation and Reasoning (KR), Allen, James and Fikes, Richard and Sandewall, Erik (Eds.), pp. 376-386 1991.
Using Explanation-Based and Empirical Methods in Theory Revision 1991
Dirk Ourston, PhD Thesis, Department of Computer Science, University of Texas at Austin.
Using Marker-Based Genetic Encoding Of Neural Networks To Evolve Finite-State Behaviour 1991
Brad Fullmer and Risto Miikkulainen, In Toward a Practice of Autonomous Systems: {P}roceedings of the First {E}uropean Conference on Artificial Life, Francisco J. Varela and Paul Bourgine (Eds.), pp. 255-262, Cambridge, MA 1991. ...
A PDP Architecture For Processing Sentences With Relative Clauses 1990
Risto Miikkulainen, In Proceedings of the 13th International Conference on Computational Linguistics (COLING-90), pp. 201--206, Helsinki, Finland: Yliopistopaino 1990.
Access-Limited Logic: A Language for Knowledge Representation 1990
James Crawford, PhD Thesis, Department of Computer Sciences, University of Texas at Austin. UT Artificial Intelligence TR AI90-141.
Changing the Rules: A Comprehensive Approach to Theory Refinement 1990
D. Ourston and Raymond J. Mooney, In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), pp. 815-820, Boston, MA, July 1990.
Concept Learning and Heuristic Classification in Weak-Theory Domains 1990
R. Bareiss, Bruce Porter and R. Holte, Artificial Intelligence, Vol. 45 (1990), pp. 229-263.
DISCERN: A Distributed Artificial Neural Network Model Of Script Processing And Memory 1990
Risto Miikkulainen, PhD Thesis, University of California. 334.
Distributed Connectionist Knowledge Representations in Script/Goal-Based Story Understanding 1990
Geunbae Lee and Risto Miikkulainen, In Proceedings of Seoul International Conference on Natural Language Processing (SICONLP-90), pp. 339-350, Seoul, Korea 1990. Seoul National University Language Research Institute.
Learning Plan Schemata From Observation: Explanation-Based Learning for Plan Recognition 1990
Raymond J. Mooney, Cognitive Science, Vol. 14, 4 (1990), pp. 483-509.
On Open Defaults 1990
Vladimir Lifschitz, In Computational Logic: Symposium Proceedings, Lloyd, John (Eds.), pp. 80-95 1990. Springer.
On the Role of Coherence in Abductive Explanation 1990
Hwee Tou Ng and Raymond J. Mooney, In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), pp. 337--342, Boston, MA, July 1990.
QPC: a compiler from physical models into qualitative differential equations 1990
J. M. Crawford, A. Farquhar, Benjamin J. Kuipers, In Proceedings of the Eighth National Conference on Artificial Intelligence (AAAI-90), pp. 365-372, Boston, MA 1990.
Script Recognition With Hierarchical Feature Maps 1990
Risto Miikkulainen, Connection Science, Vol. 2 (1990), pp. 83-101.
Understanding Natural Language with Diagrams 1990
Gordon Novak and William Bulko, In Proc. National Conference on Artificial Intelligence (AAAI-90), pp. 465-470, Boston, MA, August 1990.
An Experimental Comparison of Symbolic and Connectionist Learning Algorithms 1989
Raymond J. Mooney, J.W. Shavlik, G. Towell and A. Gove, In Proceedings of the Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), pp. 775-780, Detroit, MI, August 1989. Reprinted in ``Readings in Machine Learning'', Jude ...
Benchmark Problems for Formal Nonmonotonic Reasoning 1989
Vladimir Lifschitz, In Proceedings of the Second international Workshop on Non-monotonic Reasoning, pp. 202--219 1989.
Controlling Search for the Consequences of New Information during Knowledge Integration 1989
K. Murray and Bruce Porter , In Proceedings of the Sixth International Workshop on Machine Learning, pp. 290-295, Ithaca, NY, June 1989.
Processing Issues in Comparisons of Symbolic and Connectionist Learning Systems 1989
Douglas Fisher, Kathleen McKusick, Raymond J. Mooney, Jude W. Shavlik, and Geoffrey Towell, In Proceedings of the Sixth International Workshop on Machine Learning, pp. 169--173, Ithaca, New York 1989.
The Effect of Rule Use on the Utility of Explanation-Based Learning 1989
Raymond J. Mooney, In Proceedings of the 11th International Joint Conference on Artificial Intelligence, pp. 725-730 1989. San Francisco, CA: Morgan Kaufmann.
Toward a theory of access-limited logic for knowledge representation 1989
J. M. Crawford and Benjamin J. Kuipers, In Proceedings of the First International Conference on Principles of Knowledge Representation and Reasoning (KR'89), Los Altos, CA 1989. Morgan Kaufmann.
A General Explanation-Based Learning Mechanism and its Application to Narrative Understanding 1988
Raymond J. Mooney, Ph.D. thesis, Department of Computer Science, University of Illinois at Urbana-Champaign, 1988
A robust qualitative method for spatial learning in unknown environments 1988
Benjamin J. Kuipers and Y.-T. Byun. , In Proceedings of the National Conference on Artificial Intelligence (AAAI-88) 1988.
Generalizing the Order of Operators in Macro-Operators 1988
Raymond J. Mooney, In Proceedings of the Fifth International Conference on Machine Learning (ICML-88), pp. 270-283, Ann Arbor, MI, June 1988.
The Stable Model Semantics for Logic Programming 1988
Michael Gelfond and Vladimir Lifschitz, In Proceedings of International Logic Programming Conference and Symposium, Kowalski, Robert and Bowen, Kenneth (Eds.), pp. 1070-1080 1988. MIT Press.
Integrated Learning of Words and their Underlying Concepts 1987
Raymond J. Mooney, In Proceedings of the Ninth Annual Conference of the Cognitive Science Society, pp. 947-978, Seattle, WA, July 1987.
On the Semantics of STRIPS 1987
Vladimir Lifschitz, In Reasoning about Actions and Plans, Georgeff, Michael and Lansky, Amy (Eds.), pp. 1-9, San Mateo, CA 1987. Morgan Kaufmann.
Schema Acquisition from One Example: Psychological Evidence for Explanation-Based Learning 1987
W. Ahn, Raymond J. Mooney, W.F. Brewer and G.F. DeJong, In Proceedings of the Ninth Annual Conference of the Cognitive Science Society, pp. 50-57, Seattle, WA, July 1987.
A Domain Independent Explanation-Based Generalizer 1986
Raymond J. Mooney and S.W. Bennett, In Proceedings of the Fifth National Conference on Artificial Intelligence (AAAI-86), pp. 551-555, Philadelphia, PA, August 1986.
Explanation-Based Learning: An Alternative View 1986
G.F. DeJong and Raymond J. Mooney, Machine Learning (1986), pp. 145-176.
Generalizing Explanations of Narratives into Schemata 1985
Raymond J. Mooney, Masters Thesis, Department of Computer Science, University of Illinois at Urbana-Champaign.
Generalizing Explanations of Narratives into Schemata 1985
Raymond J. Mooney, In Proceedings of the Third International Machine Learning Workshop, pp. 126--128, New Brunswick, New Jersey 1985.
Learning Schemata for Natural Language Processing 1985
Raymond J. Mooney and Gerald F. DeJong, In Proceedings of the Ninth International Joint Conference on Artificial Intelligence (IJCAI-85), pp. 681-687, Los Angeles, CA, August 1985.
The Map-Learning Critter 1985
Benjamin Kuipers, Technical Report AI TR 85-17, University of Texas at Austin, Artificial Intelligence Laboratory.
Data Abstraction in GLISP 1983
Gordon Novak, SIGPLAN Notices, Vol. 18, 6 (1983), pp. 170-177.
GLISP: A Lisp-based Language with Data Abstraction 1983
Gordon Novak, A. I. Magazine, Vol. 4, 3 (1983), pp. 37-47.
GLISP: A Lisp-based Programming System with Data Abstraction 1983
Gordon S. Novak Jr., The AI Magazine, Vol. 4, 3 (1983), pp. 37--47.
Knowledge Based Programming Using Abstract Data Types 1983
Gordon Novak, In Proc. National Conference on Artificial Intelligence (AAAI-83), pp. 288-291, Washington, DC, August 1983.
Modeling human knowledge of routes: partial knowledge and individual variation 1983
Benjamin J. Kuipers, In Proceedings of the National Conference on Artificial Intelligence (AAAI-83) 1983. Morgan Kaufmann.
The cognitive map: Could it have been any other way? 1983
Benjamin J. Kuipers, In Spatial Orientation: Theory, Research, and Application, H. L. Pick, Jr. and L. P. Acredolo (Eds.), pp. 345--359, New York 1983. Plenum Press.
GLISP: A High-Level Language for A.I. Programming 1982
Gordon Novak, In Proc. National Conference on Artificial Intelligence (AAAI-82), pp. 238-241, Pittsburgh, PA, August 1982.
The `Map in the Head' metaphor 1982
Benjamin J. Kuipers, Environment and Behavior, Vol. 14 (1982), pp. 202--220.
GLISP: An Efficient, English-like Programming Language 1981
Gordon Novak, In Proc. Third Annual Conference of the Cognitive Science Society, Berkeley, CA, August 1981.
Research on Expert Problem Solving in Physics 1980
Gordon Novak and Agustin Araya, In Proc. First Annual National Conference on Artificial Intelligence (AAAI-80), Stanford, CA, August 1980.
Commonsense knowledge of space: learning from experience 1979
Benjamin J. Kuipers, In Proceedings of the Sixth International Joint Conference on Artificial Intelligence (IJCAI-79) 1979. Morgan Kaufmann. Reprinted in Advances in Spatial Reasoning, Volume 2, Su-shing Chen (Ed.)...
On representing common sense knowledge 1979
Benjamin J. Kuipers, In Associative Networks: The Representation and Use of Knowledge by Computers, N. V. Findler (Eds.), pp. 393--408, New York 1979. Academic Press.
Modeling spatial knowledge 1978
Benjamin J. Kuipers, Cognitive Science, Vol. 2 (1978), pp. 129--153.
Representations of Knowledge in a Program for Solving Physics Problems 1977
Gordon Novak, In Proc. 5th International Joint Conference on Artificial Intelligence (IJCAI-77), pp. 286-291, Cambridge, MA, August 1977.
Representing Knowledge of Large-Scale Space 1977
Benjamin J. Kuipers, PhD Thesis, Mathematics Department, Massachusetts Institute of Technology. Published as Technical Report 418, M.I.T. Artificial Intelligence Laboratory, 1977.
Computer Understanding of Physics Problems Stated in Natural Language 1976
Gordon Novak, American Journal of Computational Linguistics, 53 (1976).