TDDE13 Multiagent Systems
The examination consists of two parts:
LAB1 (2 ECTS)
Complete the two lab assignments.
UPG1 (4 ECTS)
Attend the two first seminars; solve and submit the home exercises before deadline; and write an individual report on a subject in multi-agent systems of your choice (a subject which you shall present at one of the two last seminars). Note that you need approval from the examinator or your TA on the subject you choose!
There are two lab sessions in the course:
Centralized Coordination Algorithms Lab
Download the instructions here.
New for this year is that this lab will use the online judge Kattis for code approval (see this webpage for more information).
Use this Kattis C++ input/output handler if you wish.
To pass this lab, you need your Kattis submissions accepted before the deadline. You do not need to write a report for this lab.
Multi-agent Reinforcement Learning Lab
Download the instructions here.
To pass this lab, you need your lab report approved by your TA.
UPG1To pass UPG1, you need to complete the exercise sets (14 points in total) and write an individual report (14 points in total). Grades are given as follows:
Exercise Sets (UPG1)
There are two exercise sets in the course; one for each of the two first seminars:
- Exercise Set 1 - Agents and Game Theory (7 points total)
- Exercise Set 2 - Mechanism Design, Social Choice and Coalitional Game Theory (7 points total)
Individual Report (UPG1)
To pass UPG1, you must also write an individual report on a subject related to multi-agent systems that you find interesting. You need to cite at least two published papers from well-known venues/journals. The report should be at maximum 3 pages (excluding references). It is important that you formulate yourself concisely and think carefully about what to include! You can choose any subject related to multi-agent systems, but here are a few suggestions (with sample papers for inspiration):
- Cooperative Games, Coalition Formation, Coordination and Organizations
- Ferber, Jacques, Olivier Gutknecht, and Fabien Michel. "From agents to organizations: an organizational view of multi-agent systems." International workshop on agent-oriented software engineering. Springer, Berlin, Heidelberg, 2003.
- Shehory, Onn, and Sarit Kraus. "Methods for task allocation via agent coalition formation." Artificial intelligence 101.1-2 (1998): 165-200.
- Kelso Jr, Alexander S., and Vincent P. Crawford. "Job matching, coalition formation, and gross substitutes." Econometrica: Journal of the Econometric Society (1982): 1483-1504.
- Bolger, Edward M. "A value for games with n players and r alternatives." International Journal of Game Theory 22.4 (1993): 319-334.
- Myerson, Roger B. "Values of games in partition function form." International Journal of Game Theory 6.1 (1977): 23-31.
- Thrall, Robert M., and William F. Lucas. "N-person games in partition function form." Naval Research Logistics Quarterly 10.1 (1963): 281-298.
- Sandholm, Tuomas, et al. "Coalition structure generation with worst case guarantees." Artificial Intelligence 111.1-2 (1999): 209-238.
- Multi-Agent Learning
- Panait, Liviu, and Sean Luke. "Cooperative multi-agent learning: The state of the art." Autonomous agents and multi-agent systems 11.3 (2005): 387-434.
- Shoham, Yoav, Rob Powers, and Trond Grenager. "If multi-agent learning is the answer, what is the question?" Artificial Intelligence 171.7 (2007): 365-377.
- Leibo, Joel Z., et al. "Multi-agent reinforcement learning in sequential social dilemmas." Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. International Foundation for Autonomous Agents and Multiagent Systems, 2017.
- Non-Cooperative Games, Utility Theory, Values and Equilibrium
- Nash, John. "Non-cooperative games." Annals of mathematics (1951): 286-295.
- Von Neumann, John, Oskar Morgenstern, and Harold William Kuhn. Theory of games and economic behavior (commemorative edition). Princeton university press, 2007.
- Fishburn, Peter C. "Retrospective on the utility theory of von Neumann and Morgenstern." Journal of Risk and Uncertainty 2.2 (1989): 127-157.
- Axtell, Robert L. "Non-cooperative dynamics of multi-agent teams." Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3. ACM, 2002.
Seminar Presentation (UPG1)To pass the course, you also have to give a 10 minute presentation of your subject of choice (i.e., the one you are writing the individual report on) at one of the seminars. This presentation should be aimed at your fellow students, so that they can understand and grasp the main ideas and concepts of your individual report.
Rules for examination of computer lab assignments at IDA
You are expected to do lab assignments in group or individually, as instructed for a course. However, examination is always based on individual performance.
It is not allowed to hand in solutions copied from other students, or from elsewhere, even if you make changes to the solutions. If there is suspicion of such, or any other form of cheating, teachers are obliged to report it to the University Disciplinary Board.
Be prepared to answer questions about details in specific code and its connection to theory. You may also be asked to explain why you have chosen a specific solution. This applies to all group members.
If you foresee problems meeting a deadline, contact your teacher. You can then get some help and maybe the deadline can be set to a later date. It is always better to discuss problems, instead of, e.g., to cheat.
Any kind of academic dishonesty, such as cheating, e.g. plagiarism or use of unauthorized assistance, and failure to comply with university examination rules, may result in the filing of a complaint to the University Disciplinary Board. The potential penalties include suspension, warning.
Policy for handing in computer lab assignments at IDA
For all IDA courses having computer lab assignments there will be one deadline during or at the end of the course. If you fail to make the deadline, you must retake the, possibly new, lab course the next time the course is given.
If a course deviates from this policy, information will be given on the course web pages.
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Last updated: 2020-12-03