CS344M: Autonomous Multiagent Systems -- Fall 2012: Assignments Page

Assignments for Autonomous Multiagent Systems (cs344M)

Week 1 (9/4,6): Autonomous agents

Readings
  • Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents ( Alternative link).
    Stan Franklin and Art Graesser
  • Textbook:
  • First edition: sections 1, 1.1 (pages 1-7), 2-2.6 (pages 15-36)
    **OR**
  • Second edition: sections 1, 1.1 (pages 1-8), 2-2.5 (pages 21-38)
  • Soccer Server 2D Manual and/or Soccer Server 3D Manual .
    Note that the 2D manual is fairly out of date. No need to read the manuals from cover to cover. Just become familiar with them.
    There is a more recent 2D manual here, and a more recent 3D manual here, but they are still under construction.
    •

    Exercises: (due at 9pm on Monday, 9/3)

  • Exercise 1 from Chapter 2 (p. 46) in the first edition.
    One agent not discussed in class or in the readings is sufficient.
    For those of you with the 2nd edition, here is the question:
    Give an example of an agent not discussed in the readings or in class (not necessarily intelligent) that you know of. Define as precisely as possible the following.
    (1) The environment that the agent occupies (physical, software, etc.), the states that theis environment can be in, and whether the environment is: accessible or inaccessible; deterministic or non-deterministic; episodic or non-episodic; static or dynamic; discrete or continuous.
    (2) The action repertoire available to the agent, and any preconditions associated with these actions.
    (3) The goal, or design objectives of the agent - what it is intended to achieve.
  • Send your response as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 1 readings".
  • As indicated on the course overview page, your response should be well-thought-out, coherent, and concise. Quality of written expression will be a factor in the grading (use full sentences). Short, to-the-point answers are preferred. For full credit, your email should be sent by 9pm on Monday, 9/3.
    • Programming 1: (due 12:30pm on Thursday, 9/6)
  • If you don't have a CS UNIX account (e.g. because you're a non-CS major), sign up for a temporary account IMMEDIATELY! It will take several days for the account to be activated. Also, please be aware that the account will expire and completely disappear two weeks into the spring semester.
  • The first programming assignment has 2 main parts, each with three subparts:
  • Introduction to the 2D Simulator
  • Get Familiar with the 2D soccer server.
  • Watch a game.
  • Create a game.
  • Introduction to the 3D Simulator
  • Get Familiar with the 3D soccer server.
  • Watch a game.
  • Create a game.
  • To turn in your log files use the turnin program. Submit your 2D log file to turnin with grader "eladlieb" and assignment label "prog1". Submit your 3D log file to turnin with grader "patmac" and assignment label "prog1-3D". Once you have submitted both log files to the correct turnin accounts, send us an email to that effect.

    • Week 2 (9/11,13): Agent architectures

    Jump to the resources page.

    Readings

  • Intelligence without Representation.
     Rodney A. Brooks.
    Artificial Intelligence 47 (1991), 139-159.
  • Experiences with an Architecture for Intelligent, Reactive Agents.
     R. Peter Bonasso, R. James Firby, Erann Gat, David Kortenkamp, David P. Miller, and Marc G. Slack.
    JETAI 9(2/3):237-256, 1997.
    (You can skim section 3. Focus on the contrast with the first article.)
  • The RoboCup Synthetic Agent Challenge 97.
    Hiroaki Kitano, Milind Tambe, Peter Stone, Manuela Veloso, Silvia Coradeschi, Eiichi Osawa, Hitoshi Matsubara, Itsuki Noda, and Minoru Asada.
    Fifteenth International Joint Conference on Artificial Intelligence (IJCAI-97).
    HTML version
    • Exercises: (due at 9pm on Monday 9/10)
  • Identify one way in which 3T departs from Brooks' design principles for his creatures.
    **AND** (optional)
    Send a free-form response to the readings (see the syllabus).
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 2 readings".
    •

    Programming 2: (due at 12:30pm on Thursday, 9/13)

  • You may choose whether you wish to do the 2D version or the 3D version of programming assignment 2 (or you can do both for extra credit).
  • The 2D version has 3 main tasks:
  • Score a goal.
  • 1 on 1.
  • Passing.
  • The 3D version has 3 main tasks:
  • Score a goal.
  • 1 on 1.
  • Passing.
  • To turn in your files, use the turnin program. Use assignment label "prog2" and grader "eladlieb" if you are submitting the 2D version of the assignment. Use assignment label "prog2-3D" and grader "patmac" if you are submitting the 3D version. Once you have submitted your assignment, send us an email to that effect with a brief description of your approach.

    • Week 3 (9/18,20): Multiagent systems

    Jump to the resources page.

    Readings

  • MultiAgent Systems.
     Katia Sycara.
    AI Magazine, 1998.
  • The above is an overview of multiagent systems. Another overview (optional):
    Multiagent Systems: A Survey from a Machine Learning Perspective.
     Peter Stone and Manuela Veloso.
    Autonomous Robots, volume 8, number 3, July 2000.
    •
  • Designing and Understanding Adaptive Group Behavior.
    Maja J Mataric.
    Adaptive Behavior 4:1, Dec 1995, 51-80.
  • The CMUnited-98 Champion Simulator Team.
     Peter Stone, Manuela Veloso, and Patrick Riley.
    in RoboCup-98: Robot Soccer World Cup II, M. Asada and H. Kitano (eds.), 1999. Springer Verlag, Berlin.
  • Another team paper (optional):
    Austin Villa 2012: Standard Platform League World Champions.
    Samuel Barrett, Katie Genter, Yuchen He, Todd Hester, Piyush Khandelwal, Jacob Menashe, and Peter Stone.
    to appear.
    •
    • Exercises: (due at 9pm on Monday 9/17)
  • Respond to the readings in some way (free-form response). If you're stuck, you can answer the question from last year: Think of an application that could be implemented as a multiagent system or a single agent. Briefly describe the 2 approaches you envision and list/discuss some of their relative merits.
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 3 readings".
    •

    Programming 3: (due at 12:30pm on Thursday, 9/20)

  • This week's programming assignment is to use communication among agents (in soccer simulation) to help an agent improve its performance at some task such as keeping track of where the ball is.
  • You are highly encouraged to use the opposite simulator than what you did for assignment 2. To encourage you, if you choose to use the same simulator as last week, then you must also improve assignment 2's passing task by using communication to aid in passing accuracy and/or maintaining adequate spacing. Similarly to last week, there is extra credit for doing both the 2D and 3D versions of the assignment.
  • 2D version
  • 3D version
  • To turn in your files, use the turnin program. Use assignment label "prog3" and grader "eladlieb" if you are submitting the 2D version of the assignment. Use assignment label "prog3-3D" and grader "patmac" if you are submitting the 3D version.
  • Once you have turned in your files, send us an email to that effect, clearly stating whether you submitted a 2D or 3D version of the assignment in your subject. Be sure to include a brief description of your task, your communication protocol, and an answer to the following question: 'Could an opponent agent disrupt your communication method? How?' in your email.

    • Week 4 (9/25,27): Agent communication and Teamwork

    Jump to the resources page.

    Readings

  • A Review and Development of Agent Communication Language.
     Moamin Ahmed, Mohd Sharifuddin Ahmad, and Mohd Zaliman Mohd Yusoff.
    electronic Journal of Computer Science and Information Technology, 2009.
  • On Team Formation.
    Cohen, P. R., Levesque, H. R., and Smith, I.
    in Hintikka, J. and Tuomela, R. (Eds.) Contemporary Action Theory. Synthese, 1997.
  • Supplemental (optional) readings are on the class resources page. At least look at the abstracts to see if you're interested in reading them.
    • Exercises: (due at 9pm on Monday)
  • Respond to the readings in some way (free-form response). One acceptable response is to answer one of the questions from last year:
  • Programming assignment 3 was to use communication to help soccer agents improve at some task. Will an ACL be useful to you as you work in these domains? Why or why not?
  • Choose a domain or example not discussed in the readings and briefly describe how it could be represented in terms of joint intentions.
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 4 readings".
    •

    Programming 4: (due at 12:30pm on next Thursday, 10/4)

  • The programming assignment for this week and the next is to get familiar with one of the 2D or 3D code bases and use it to create a simple team capable of playing a full soccer game.
  • 2D version - Helios
  • 3D version - UT Austin Villa
  • To turn in your files, use the turnin program. Use assignment label "prog4" and grader "eladlieb" if you are submitting the 2D version of the assignment. Use assignment label "prog4-3D" and grader "patmac" if you are submitting the 3D version. Once the assignment is there, send us an email to that effect. Be sure to include a brief description of what your team does in your email.

    • Week 5 (10/2,4): RoboCup case studies

    Jump to the resources page.

    Readings

  • Read all the ABSTRACTS and then choose ANY TWO (2) of the following RoboCup case studies, or supplementary papers on the resources page (to help you think about your proposal). Also read AT LEAST ONE 2012 team description paper (see the resources page) from either the 2D or 3D league.

  • Evolving Team Darwin United.
     David Andre and Astro Teller.
    in Asada, M. (ed) Robocup-98: Robot Soccer World Cup II. Springer-Verlag, Berlin, 1999.
    (1998 evolutionary learning approach)
  • An Architecture for Action Selection in Robotic Soccer.
     Peter Stone and David McAllester.
    In Proceedings of the Fifth International Conference on Autonomous Agents, 2001.
  • An Empirical Study of Coaching.
     Patrick Riley, Manuela Veloso, and Gal Kaminka.
    In H. Asama, T. Arai, T. Fukuda, and T. Hasegawa, editors, Distributed Autonomous Robotic Systems 5,pp. 215-224, Springer-Verlag, 2002.
    (2001 coach competition champion)
  • The UT Austin Villa 2003 Champion Simulator Coach: A Machine Learning Approach.
     Gregory Kuhlmann, Peter Stone, and Justin Lallinger.
    In Daniele Nardi, Martin Riedmiller, and Claude Sammut, editors, RoboCup-2004: Robot Soccer World Cup VIII, Springer Verlag, Berlin, 2005. To appear.
    (2003 coach competition champion)
  • Effective Methods for Reinforcement Learning in Large Multi-Agent Domains
     Daniel Withopf and Martin Riedmiller.
    Information Technology Journal. 47 (2005) 5
    (2005 2D simulation champion)
  • UT Austin Villa 2011: A Champion Agent in the RoboCup 3D Soccer Simulation Competition
     Patrick MacAlpine, Daniel Urieli, Samuel Barrett, Shivaram Kalyanakrishnan, Francisco Barrera, Adrian Lopez-Mobilia, Nicolae Stiurca, Victor Vu, and Peter Stone.
    In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2012.
    (2011 3D simulation champion)
  • Controlled Kicking under Uncertainty
     Samuel Barrett, Katie Genter, Todd Hester, Michael Quinlan, and Peter Stone.
    In The Fifth Workshop on Humanoid Soccer Robots at Humanoids 2010, December 2010.
    (Part of our winning physical robot (Standard Platform League) strategy)
    • Exercises: (due at 9pm on Monday)
  • Free-form response.
    **OR**
    For each of the two articles you chose to read, list the strengths of the described approach with respect to that in the other article. That is, what aspects of the complete task does it focus on that are ignored by the other approach, what unique techniques are used, or what does it do particularly well.
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 5 readings".
    •

    Programming 4: (due at 12:30pm on Thursday, 10/4)

  • See "Week 4" above.

    • Week 6 (10/9,11): Swarms and self-organization

    Jump to the resources page.

    Readings

  • "Go to the Ant": Engineering Principles from Natural Agent Systems. H. Van Dyke Parunak.
    Annals of Operations Research, 75:69-101, 1997.
  • Robust and Efficient Covering of Unknown Continuous Domains with Simple, Ant-Like A(ge)nts.
     Eliyahu Osherovich, Vladimir Yanovki, Israel A.Wagner, and Alfred M. Bruckstein.
    The International Journal of Robotics Research Vol. 27, No. 7, July 2008, pp. 815-831.
    • Exercises: (due at 9pm on Monday)
  • Free-form response.
    **OR**
    Think of an application not discussed in the readings that you think could be better implemented with lots of simple agents rather than a small number of more cognitive agents. Describe and compare the merits of the two possible approaches.
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 6 readings".
    •

    Final Project Proposal: (due at 12:30pm on Thursday, 10/11)

  • See the final project page for full details.

    • Week 7 (10/16,18): Applications

    Jump to the resources page.

    Readings

  • Coordinating Hundreds of Cooperative, Autonomous Vehicles in Warehouses.
    Peter R.Wurman, Raffaelo D'Andrea, and Mick Mountz.
    AAAI Magazine, 2007.
  • A Multiagent Approach to Autonomous Intersection Management.
     Kurt Dresner and Peter Stone.
    Journal of Artificial Intelligence Research, 31:591-656.
    • Exercises: (due at 9pm on Monday)
  • Free-form response.
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 7 readings".
    •

    Survey: (due at 9pm on Wednesday)

  • Complete the midterm course evaluation survey by Wednesday night at 9pm.

    • Week 8 (10/23,25): Game Theory

    Jump to the resources page.

    Survey: If you haven't done so, please complete the midterm course evaluation survey.

    Readings

  • Textbook: chapter 11 (recommended) [chapter 6 in the first edition]
    **AND/OR**
    Roger McCain's introduction to game theory. [alternative link] .
  • Beginning to "Games with More than One Equilibrium"
  • "Cooperative Games"
  • "Sequential Games"

    • McCain motivates game theory from an economic perspective involving people as the actors as opposed to the textbook which motivates it from the AI agent perspective. But the theory is the same.

    • Exercises: (due at 9pm on Monday)
  • Free-form response
    **OR**
    Identify an application or situation not discussed in the reading that could be modeled as a matrix game. Specify the game matrix and identify all the dominant strategies and (pure strategy) Nash equilibria, if any.
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 8 readings".
    •

    Final Project Progress Report: (due at 12:30pm on Thursday, 11/8)

  • See the final project page for full details.

    • Survey: (due at 12:30pm on Thursday, 10/25)

  • Complete the midterm course evaluation survey.
    (this is instead of a programming assignment this week!)

    • Week 9 (10/30,11/1): Game theory II + Statistical Measurements

    Jump to the resources page.

    Readings

  • Read this introduction to statistical significance.
  • Scan a chart indcating the range of existing statistical tests.
  • Search on the web to familiarize yourself with at least:
  • Standard deviation
  • Student's t-test
  • Paired t-test
  • Chi-square test
    • Exercises: (due at 9pm on Monday)
  • Describe two experiments that you could do as a part of your final project, one of which could use a t-test, and one of which could use a paired t-test to measure significance. Be sure to specify your experimental setup and the null hypothesis. Bonus (2 points): do the same for the Chi-square test.
    **AND** (optional)
    Free-form response
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 9 readings".
    •

    Final Project Progress Report: (due at 12:30pm on Thursday, 11/8)

  • See the final project page for full details.

    • Week 10 (11/6,8): Distributed rational decision making

    Jump to the resources page.

    Readings

  • Distributed Rational Decision Making. Focus on Sections 5.1 - 5.5, but at least skim the rest.
    Tuomas Sandholm.
    (also available form citeseer)
    In the textbook Multiagent Systems: A Modern Introduction to Distributed Artificial Intelligence, Weiss, G., ed., MIT Press. p. 201-258.
    • Exercises: (due at 9pm on Monday)
  • Free-form response.
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 10 readings".
    •

    Final Project Progress Report: (due at 12:30pm on Thursday, 11/8)

  • See the final project page for full details.

    • Week 11 (11/13,15): Auctions

    Jump to the resources page.

    Readings

  • Selling Spectrum Rights.
     John McMillan.
    Journal of Economic Perspectives, 8(3):145-162, 1994.
  • The 2001 Trading Agent Competition.
    Michael P. Wellman, Amy Greenwald, Peter Stone, and Peter R. Wurman.
    Fourteenth Innovative Applications of Artificial Intelligence Conference(IAAI-2002)
    • Exercises: (due at 9pm on Monday)
  • Free-form response
    **AND/OR**
    Suggest a use for agents in the FCC spectrum auction design described in the first reading.
    **AND/OR**
    Suggest a change in TAC that would make the game more interesting or realistic in some way. In either case, briefly motivate the need for your suggestion and describe how your change addresses this need.
    Regardless, make sure you show evidence that you read both papers!
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 11 readings".
    •

    Progress Report Peer Reviews: (due at 12:30pm on Thursday, 11/15)

  • See the final project page for full details.

    • Week 12 (11/20): Agent modeling

    Jump to the resources page.

    Readings

  • Recursive agent modeling using limited rationality. (citeseer link)
    Jose M. Vidal and Edmund H. Durfee.
    In Proceedings of the First International Conference on Multi-Agent Systems (ICMAS-95), pages 376-383, Menlo Park, California, June 1995. AAAI Press.
  • Learning Teammate Models for Ad Hoc Teamwork.
    Samuel Barrett and Peter Stone
  • Scan the titles of the papers in the technical programs of the recent series of workshops on opponent modeling:
  • PAIR 2011
  • PAIR 2010
  • PAIR 2009
  • PAIR 2007
  • MOO 2006
  • MOO 2005
  • MOO 2004
  • **OPTIONAL**: If you'd like, you may replace one of the above 2 assigned readings with a paper from one of these workshops. If so, please indicate which one you read in your reading response. Regardless, you should at least read the abstracts of the 2 assigned readings.
    • Exercises: (due at 9pm on Monday)
  • Free-form response
    **AND/OR**
    Think of a domain not in the readings in which you could benefit from agent modeling. Briefly outline approaches with and without modeling and explain what benefits you would expect in the modeling case.
    Regardless, make sure you show evidence that you read both papers!
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 12 readings". Please also cc: sbarrett@cs.utexas.edu
    •

    Final Project: (due at 12:30pm on Tuesday, 12/4)
    Final Project Report: (due at 12:30pm on Thursday, 12/6)

  • See the final project page for full details.

    • Week 13 (11/27,29): Multiagent Learning

    Jump to the resources page.

    Readings

  • New Methods for Competitive Coevolution.
     Christopher D. Rosin and Richard K. Belew.
    Extended version of paper from Proceedings of the Sixth International Conference on Genetic Algorithms, 1995.
  • Scaling Reinforcement Learning toward RoboCup Soccer.
    Peter Stone and Richard S. Sutton.
    In Proceedings of the Eighteenth International Conference on Machine Learning, pp. 537-544, Morgan Kaufmann, San Francisco, CA, 2001.
    • Exercises: (due at 9pm on Monday)
  • Free-form response
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 13 readings".

    • Final Project: (due at 12:30pm on Tuesday, 12/4)
    Final Project Report: (due at 12:30pm on Thursday, 12/6)

  • See the final project page for full details.

    • Week 14 (12/4, 12/6): Entertainment Agents

    Jump to the resources page.

    Readings

  • Read all the ABSTRACTS and then choose ANY ONE (1) of the following papers. If you have time and are interested, by all means read more. Otherwise, file them away and read the ones you're interested in when you have a chance. These are all super-fun papers!

  • A Social Reinforcement Learning Agent.
     Charles Lee Isbell Jr., Christian R. Shelton, Michael Kearns, Satinder Singh, and Peter Stone.
    Fifth International Conference on Autonomous Agents, 2001.
  • Tears and Fears: Modeling emotions and emotional behaviors in synthetic agents.
     Jonathan Gratch and Stacy Marsella.
    Fifth International Conference on Autonomous Agents, 2001.
  • Evolving Neural Network Agents in the Nero Video Game.
     Kenneth O. Stanley, Bobby D. Bryant, and Risto Miikkulainen.
    Proceedings of the IEEE 2005 Symposium on Computational Intelligence and Games (CIG'05). Piscataway, NJ: IEEE, 2005.
  • Gesture-based Human-Robot Jazz Improvisation.
     Guy Hoffman and Gil Weinberg.
    International Conference on Robotics and Automation, 2010.
    • Exercises: (due at 9pm on Monday)
  • Free-form response
    *** AND ***
    Choose a recent chatbot from:
  • Elbot
  • Artificial Solutions
  • Hal
  • Find one on chatbots.org (Scroll down to "Examples of Chatbots"
  • Find one on the Loebner competition page
    • Interact with it for at least 10 minutes. What is it able to do? What kinds of things get it totally hosed?
  • Send your responses as ASCII text (not encoded in any way) to todd@cs.utexas.edu, eladlieb@cs.utexas.edu, and patmac@cs.utexas.edu with subject: "Week 14 readings".
    •

    Final Project: (due at 12:30pm on Tuesday, 12/4)
    Final Project Report: (due at 12:30pm on Thursday, 12/6)

  • See the final project page for full details.

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