Course Description: The goal of this class is to provide a broad and rigorous introduction to the theory, methods and algorithms of multi-agent systems. The material spans disciplines as diverse as engineering (including control theory and signal processing), computer science (including artificial intelligence, algorithms and distributed systems), micro-economic theory, operations research, public policies, psychology and belief systems. A primary focus of the course is on the application of cooperative and non-cooperative game theory for both static and dynamic models, with deterministic as well as stochastic descriptions. The coverage will encompass both theoretical and algorithmic developments, with multi-disciplinary applications.
Prerequisites: The course is offered as a graduate level course. To follow the course, familiarity with dynamic systems (at the level of EL-GY 6253), some background in probability theory (at the level of EL-GY 6303) are required. Some familiarity with the basics of linear and nonlinear programming is desirable but not required. A minimum GPA of 3.5 is required for undergraduates to take the course.
Midterm Exam: 20%
Take-home Final Exam: 20%
Term Project: 30%
[BO] T. Başar and G.J. Olsder, Dynamic Noncooperative Game Theory, 2nd edition, Classics in Applied Mathematics, SIAM, Philadelphia, 1999
[FT] D. Fudenberg and J. Tirole, Game Theory, MIT Press, 1991.
[OW] G. Owen, Game Theory, 4th edition, Academic Press, 2013.
[RG] R. Gibbons, Game Theory for Applied Economists, Princeton University Press, 1992.
[MS] M. Maschler and E. Solan, Game Theory, Cambridge University Press, 2013.
[RI] R. Isaacs, Differential Games, Kruger, NY, 2nd ed., 1975 (First edition: Wiley, NY, 1965).
[VM] J. von Neumann and O. Morgenstern, Theory of Games and Economic Behavior, Princeton University Press, Princeton, NJ, 2nd ed., 1947 (first edition: 1944).
[VB] T. L. Vincent and J. S. Brown, Evolutionary Game Theory, Natural Selection, and Darwinian Dynamics, Cambridge University Press, Cambridge, England, 2005.
[BB] T. Başar and P. Bernhard, H-infinity Optimal Control and Related Minimax Design Problems: A Dynamic Game Approach, 2nd edition, Birkhäuser, Boston, MA, August 1995.
[CBL] N. Cesa-Bianchi and G. Lugosi, Prediction, Learning, and Games, Cambridge University Press, 2006.
[MOJ] M. O. Jackson, Social and Economic Networks, Princeton University Press, 2010
[OR] M. J. Osborne and A. Rubinstein, A Course in Game Theory, MIT Press, 1994
[DBP] D. P. Bertsekas, Dynamic Programming and Optimal Control, Athena Scientific; 4th edition, 2007
[VK] V. Krishna, Auction Theory, Second Edition, Academic Press, 2009
[VNRT] V. Vazirani, N. Nisan, T. Roughgarden, and E. Tardos, Eva, Algorithmic Game Theory, Cambridge, UK: Cambridge University Press, 2007.