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.

Grading:

Homework: 30%

Midterm Exam: 20%

Take-home Final Exam: 20%

Term Project: 30%

Required Text:

[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.

Supplementary Text:

[RG]     R. Gibbons, Game Theory for Applied Economists, Princeton University Press, 1992.

[MS]     M. Maschler and E. Solan, Game Theory, Cambridge University Press, 2013.

Additional References:

[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.