Bo Liu
Ph.D. Student
Publications
     [Expand to show all 23][Minimize]
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.
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.
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.
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.
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).
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.
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.
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.
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).
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).
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).
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.
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.
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.
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.
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.
Team Orienteering Coverage Planning with Uncertain Reward 2021
Bo Liu, Xuesu Xiao, and Peter Stone, No other information
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).
APPLD: Adaptive Planner Parameter Learning from Demonstration 2020
Xuesu Xiao, Bo Liu, Garrett Warnell, Jonathan Fink, and Peter Stone, No other information
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.
Labs
Currently affiliated with Statistical Learning and AI