Equilibria for Games with Asymmetric Information: from guesswork to systematic evaluation

We consider problems involving multiple agents making decisions dynamically in the presence of asymmetric information. When agents have a common objective (dynamic decentralized teams) recent results have established a systematic framework for obtaining the optimal decision strategy that is akin to the well-known backward induction in partially observed Markov decision
processes (POMDPs). However, when agents are strategic (dynamic games with asymmetric information) there is no known systematic process for evaluating the appropriate equilibria in a sufficiently general setting. The well-known backward induction process for finding sub-game perfect
equilibria is useless in these problems and we are stuck with an indecomposable fixed-point equation in the space of strategies and beliefs. For simple games usually one first guesses them and then tests if conditions are satisfied; clearly this is not a satisfactory methodology. In this talk we will discuss a class of perfect Bayesian equilibria (PBE) that are the counterparts of Markov perfect equilibria (MPE) for asymmetric information games. The corresponding "state" is a belief based on the common information among agents. We will then propose a two-step backward-forward inductive algorithm to systematically find such structured PBE. Each period in the backward induction involves solving a "small" fixed point equation.
Achilleas Anastasopoulos (S'97"“M'99"“SM'13) was born in Athens, Greece in 1971. He received the Diploma in Electrical Engineering from the National Technical University of Athens, Greece in 1993, and the M.S. and Ph.D. degrees in Electrical Engineering from University of Southern California in 1994 and 1999, respectively. He is currently an Associate Professor at the University of Michigan, Ann Arbor, Department of Electrical Engineering and Computer Science.
His research interests lie in the general area of communication theory, with emphasis in channel coding, multi-user channels, as well as connections between multi-user communications and decentralized stochastic control.
He is the co-author of the book Iterative Detection: Adaptivity, Complexity Reduction, and Applications (Reading, MA, USA: Kluwer Academic, 2001). Dr. Anastasopoulos is the recipient of the "Myronis Fellowship" in 1996 from the Graduate School at the University of Southern California, and the NSF CAREER Award in 2004. He served as a technical program committee member for ICC 2003 and Globecom 2004, 2012, and on the editorial board
of the IEEE TRANSACTIONS ON COMMUNICATIONS.