CS378: Autonomous Multiagent Systems -- Fall 2002: Assignments Page

Assignments for Autonomous Multiagent Systems (cs378)

Week 15

Readings: (due by class on Tuesday, 12/3)
  • BoB: an Interactive Improvisational Companion.
     Belinda Thom.
    Fourth International Conference on Autonomous Agents, 2000.

  • Optional READ AT LEAST THE ABSTRACTS!
    If you're on top of the final project and are interested, by all means read more. If you have time to read just one, please read the first one. Otherwise, file them away and read the ones you're interested in when you have a chance. These are all super-fun papers!
  • Tears and Fears: Modeling emotions and emotional behaviors in synthetic agents.
     Jonathan Gratch and Stacy Marsella.
    Fifth International Conference on Autonomous Agents, 2001.
  • Creatures: Artificial Life Autonomous Software Agents for Home Entertainment.
     Stephen Grand, Dave Cliff, and Anil Malhotra.
    Millenium technical report 9601, 1996.
  • 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.
    • Exercises: (due at noon on Tuesday, 12/3)
  • Think of a domain not presented in the readings (including abstracts of optional papers) in which you can have believable agents which are fun to play with and provide improvisational companionship.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 15 exercises".
    •  Final Project: (due at 2pm on Tuesday, 12/3)
    Final Project Report: (due at 2pm on Thursday, 12/5)
  • See the final project page for full details.

    • Week 14

    Readings: (due by class on Tuesday, 11/26)
  • Methods for Competitive Co-evolution: Finding Opponents Worth Beating.
     Christopher D. Rosin and Richard K. Belew.
    Proceedings of the Sixth International Conference on Genetic Algorithms, 1995.
  • Layered Learning.
     Peter Stone and Manuela Veloso.
    Eleventh European Conference on Machine Learning, 2000.
    • Exercises: (due at noon on Tuesday, 11/26)
  • Think of a domain not in the readings in which competitive co-evolution or layered learning could be usefully applied.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 14 exercises".
    •  Final Project: (due at 2pm on Tuesday, 12/3)
    Final Project Report: (due at 2pm on Thursday, 12/5)
  • See the final project page for full details.

    • Week 13

    Readings: (due by class on Tuesday, 11/19)
  • Recursive agent modeling using limited rationality. (get cached copy from upper right corner)
    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.
  • Tracking dynamic team activity.
     Milind Tambe.
    National Conference on Artificial Intelligence(AAAI), 1996.
  • On behavior classification in adversarial environments.
     Patrick Riley and Manuela Veloso.
    In Proceedings of the Fifth International Symposium on Distributed Autonomous Robotic Systems (DARS-2000), 2000.
    • Exercises: (due at noon on Tuesday, 11/19)
  • 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.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 13 exercises".
    •  Final Project: (due at 2pm on Tuesday, 12/3)
    Final Project Report: (due at 2pm on Thursday, 12/5)
  • See the final project page for full details.

    • Week 12

    Readings: (due by class on Tuesday, 11/12)
  • Selling Spectrum.
     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)
  • Optional (interesting, but not required)
  • The Timing of Bids in Internet Auctions: Market Design, Bidder Behavior, and Artificial Agents. Artificial Intelligence.
     Axel Ockenfels and Alvin E. Roth.
    AI Magazine, 23(3):79-88, Fall 2002.
    • Exercises: (due at noon on Tuesday, 11/12)
  • Suggest a use for agents in the FCC spectrum auction design described in the first reading **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.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 12 exercises".
    •  Final Project Progress Report: (due at 2pm on Thursday, 11/14)
  • See the final project page for full details.

    • Week 11

    Readings: (due by class on Tuesday, 11/5)
  • Distributed Rational Decision Making.
     Tuomas Sandholm.
    In the textbook Multiagent Systems: A Modern Introduction to Distributed Artificial Intelligence, Weiss, G., ed., MIT Press. Pp. 201-258.
    • Exercises: (due at noon on Tuesday, 11/5)
  • 2 cases:
  • If you haven't turned in your week 10 exercises, then the same assignment is still due for you during week 11 (in addition to the "everyone" part below).
  • If you did turn in your week 10 exercises, but would like to revise them based on our class discussions, do so, along with an explanation of what was wrong with your previous responses. We will base your week 10 grade on these revisions.
  • Everyone: Write a brief free-form reaction to any aspect of this week's reading (or the reading as a whole).
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 11 exercises".
    •  Final Project Progress Report: (due at 2pm on Thursday, 11/14)
  • See the final project page for full details.

    • Week 10

    Readings: (due by class on Tuesday, 10/29)
  • Textbook: chapter 6
    **OR**
    Roger McCain's introduction to game theory.
  • 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 noon on Tuesday, 10/2)
  • Identify 3 applications or situations not discussed in the reading that could be modeled as competitive, cooperative, or sequential game interactions (1 of each). Make up game matrices for each.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 10 exercises".
    •  Final Project Progress Report: (due at 2pm on Thursday, 11/14)
  • See the final project page for full details.

    • Week 9

    Readings: (due by class on Tuesday, 10/22)
  • BDI-agents: from theory to practice.
     A. S. Rao and M. P. Georgeff.
    In Proceedings of the First International Conference on Multiagent Systems (ICMAS), 1995.
  • Improving Elevator Performance Using Reinforcement Learning. (If the link doesn't work for you, it's also available from citeseer - cached copy in top right corner)
    R. Crites and A. Barto.
    In Advances in Neural Information Processing Systems 8 (NIPS8), D. S. Touretzky, M. C. Mozer, and M. E. Hasslemo (Eds.), Cambridge, MA: MIT Press, 1996, pp. 1017-1023.
  • Electric Elves : Applying Agent Technology to Support Human Organizations.
     Chalupsky, H., Gil, Y., Knoblock, C. A., Lerman, K., Oh, J., Pynadath, D., Russ, T. A., and Tambe, M.
    In proceedings of the International Conference of Innovative Application of Artificial Intelligence (IAAI'01), 2001.
    • Exercises: (due at noon on Tuesday, 10/22)
  • Identify an idea from one of the 3 applications in the readings that could be applied to one of the 2 other applications as well, and explain how it might improve (or at least change) the system.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 9 exercises".
    •  Final Project Progress Report: (due at 2pm on Thursday, 11/14)
  • See the final project page for full details.

    • Week 8

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

    Readings: (due by class on Tuesday, 10/15)

  • "Go to the Ant": Engineering Principles from Natural Agent Systems.
     H. Van Dyke Parunak.
    Annals of Operations Research, 75:69-101, 1997.
  • Blazing a trail: insect-inspired resource transportation by a robot team.
    Richard T. Vaughan, Kasper Stoy, Gaurav S. Sukhatme and Maja J Mataric.
    In Proceedings of the International Symposium on Distributed Autonomous Robot Systems, 2000.
    **OR**
    Progress in Pheromone Robotics (first link at the bottom of the page).
    D. Payton, R. Estkowski, M. Howard.
    7th International Conference on Intelligent Autonomous Systems, March 25-27, 2002, Marina del Rey, CA.
    • Exercises: (due at noon on Tuesday, 10/15)
  • 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 pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 8 exercises".
    •  Final Project Proposal: (due at 2pm on Thursday, 10/17)
  • See the final project page for full details.

    • Week 7

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

    Readings: (due by class on Tuesday, 10/8)

  • Choose ANY TWO (2) of the following RoboCup case studies (to help you think about your proposal):

  • Reactive Deliberation: An Architecture for Real-time Intelligent Control in Dynamic Environments.
     Michael K. Sahota.
    Proceedings of the Twelfth National Conference on Artificial Intelligence, 1994.
    (From the group that invented robotic soccer: pre-RoboCup)
  • Co-evolving Soccer Softbot Team Coordination with Genetic Programming.
     Sean Luke, Charles Hohn, Jonathan Farris, Gary Jackson, and James Hendler.
    in Kitano (ed.) RoboCup-97: Robot Soccer World Cup I. Springer Verlag, Berlin, 1998
    (1997 evolutionary learning approach)
  • AT Humboldt -- Development, Practice and Theory.
     Hans-Dieter Burkhard, Markus Hannebauer, Jan Wendler.
    in Kitano (ed.) RoboCup-97: Robot Soccer World Cup I. Springer Verlag, Berlin, 1998
    (1997 champion)
  • 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)
  • The CMUnited-99 Champion Simulator Team.
     Peter Stone, Patrick Riley, and Manuela Veloso.
    in M. Veloso, E. Pagello and H. Kitano (eds.) RoboCup-99: Robot Soccer World Cup III. Springer Verlag, Berlin, 2000.
    (1998, 1999 champion)
  • Learning Situation Dependent Success Rates of Actions in a RoboCup Scenario.
     Sebastian Buck, Martin Riedmiller.
    Pacific Rim International Coference on Artificial Intelligence, 2000.
    (2000 and 2001 runner-up)
  • Towards an Optimal Scoring Policy for Simulated Soccer Agents.
     Jelle R. Kok, Remco de Boer, Nikos Vlassis, and F.C.A. Groen.
    In G. Kaminka, P.U. Lima, and R. Rojas, editors, RoboCup 2002: Robot Soccer World Cup VI, pages 292-299, Fukuoka, Japan, 2002. Springer-Verlag.
    (2001 3rd place, 2002 4th place)
    • Exercises: (due at noon on Tuesday, 10/8)
  • 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 pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 7 exercises".
    •  Programming: (due at 2pm on Thursday, 10/10)
  • See "Week 6" (below)

    • Week 6

    Survey: Please complete the midterm course evaluation survey.

    Readings: (due by class on Tuesday, 10/1)

  • On Team Formation. (If the link doesn't work for you, it's also available from citeseer - top right corner)
     Cohen, P. R., Levesque, H. R., and Smith, I.
    in Hintikka, J. and Tuomela, R. (Eds.) Contemporary Action Theory. Synthese, 1997.
  • Optional (but recommended)
  • Towards Flexible Teamwork.
     Tambe, M.
    Journal of Artificial Intelligence Research (JAIR), Volume 7, pages 83-124, 1997.
    • Exercises: (due at noon on Tuesday, 10/1)
  • Choose a domain or example not discussed in the readings and briefly describe how it could be represented in terms of joint intentions and/or STEAM.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 6 exercises".
    •  Programming: (due at 2pm on Thursday, 10/10)
  • The programming assignment is to get familiar with the United-2002 code base (built on CMUnited-99) and use it to create a simple team capable of playing a full soccer game.
  • To turn in your files, use the turnin program with grader "vinay" and assignment label "prog4". When the assignment is there, send us an email to that effect.

    • Week 5

    Readings: (due by class on Tuesday, 9/24)
  • Textbook: chapter 8
    **OR**
    Sections 2.1 and 2.2 (pages 1-19) of Multiagent Systems and Societies of Agents. (get cached copy from upper right corner)
    Michael N. Huhns and Larry M. Stephens.
    Chapter 2 in Multiagent Systems, G. Weiss (ed.), MIT Press, 1998.
  • Agent Communication Languages: The Current Landscape.
     Yannis Labrou, Tim Finin, and Yun Peng.
    IEEE Inteligent Systems, March/April, 1999.
  • (OPTIONAL)
    Desiderata for Agent Communication Languages.
    James Mayfield, Yannis Labrou, and Tim Finin.
    Proceedings of the AAAI Symposium on Information Gathering from Heterogeneous, Distributed Environments, AAAI-95 Spring Symposium, Stanford University, Stanford, CA. March 27-29, 1995.
    • Exercises: (due at noon on Tuesday, 9/24)
  • Would KQML, KIF, or FIPA ACL be useful for your current programming assignment? Why or why not?
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 5 exercises".
    •  Programming: (due at 2pm on Thursday, 9/26)
  • See "Week 4" (below)

    • Week 4

    Readings: (due by class on Tuesday, 9/17)
  • 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.
    HTML version.
    • Exercises: (due at noon on Tuesday, 9/17)
  • 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 pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 4 exercises".
    •  Programming: (due at 2pm on Thursday, 9/26)
  • The programming assignment is to use communication among agents to help an agent keep track of where the ball is.
  • To turn in your files, use the turnin program with grader "vinay" and assignment label "prog3". When the assignment is there, send us an email to that effect, with a brief description of your communication protocol and an answer to the following question: Could an opponent agent disrupt your communication method? How?

    • Week 3 (9/10,12)

    Readings: (due by class on Tuesday, 9/10)
  • Intelligence without Representation.
     Rodney A. Brooks.
    Artificial Intelligence 47 (1991), 139-159.
    PDF version.
  • Pages 1-9 of Structured Control for Autonomous Robots.
    Reid Simmons.
    Structured Control for Autonomous Robots, IEEE Transactions on Robotics and Automation, 10:1, pp. 34-43, February 1994.
  • 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 by noon Tuesday, 9/10)
  • Part one of your current programming assignment can be implemented reactively in the sense that each action decision can be based solely on the most most recent sensation. Describe a non-reactive soccer-playing behavior.
  • Identify one way in which TCA departs from Brooks' design principles for his creatures.
  • Send your responses as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 2 exercises".
    •  Programming: (due at 2pm on Thursday, 9/12)
  • The programming assignment has 3 parts:
  • Score a goal.
  • 1 on 1.
  • Passing.
  • To turn in your files, use the turnin program with grader "vinay" and assignment label "prog2". When the assignment is there, send us an email to that effect.

    • Week 2 (9/3,5)

    Readings (due by class on Tuesday, 9/3):
  • Is it an Agent, or just a Program?: A Taxonomy for Autonomous Agents.
    Stan Franklin and Art Graesser
  • Textbook: sections 1, 1.1 (pages 1-7), 2-2.6 (pages 15-36)
    **OR**
    Intelligent Agents.
    M. Wooldridge
    In G. Weiss, editor: Multiagent Systems, The MIT Press, April 1999. Sections 1-1.3 (pages 1-17).
  • Soccer Server Manual (Just become familiar with it.)
    •

    Exercises (due noon on Tuesday, 9/3):

  • Exercise 1 from Chapter 1 (p. 46).
    **OR**
    Exercise 1 from "Intelligent Agents." (p. 44)
    One agent not discussed in class or in the readings is sufficient.
    Send your response as ASCII text (not encoded in any way) to pstone@cs.utexas.edu and vinay@cs.utexas.edu with subject: "Week 1 exercises".
    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 noon on Tuesday, 9/3.
    • Programming (due 2pm on Thursday, 9/5):
  • 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 programming assignment has 3 parts:
  • Get Familiar with the soccer server.
  • Watch a game.
  • Create a game.
  • To turn in your log file, rename it [yourlogin].rcg where [yourlogin] is your login ID and use the turnin program with grader "vinay" and assignment label "prog1". When the assignment is there, send us an email to that effect.
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