Title: Control Theoretic Modeling of Bounded Rationality in Games
Speaker: Jeff Shamma
Date and Time: 12/02/2021 4:10PM ET
Location: Phillips 233 and Zoom
Abstract: The classical solution concept of Nash equilibrium in game theory presumes that each agent’s decision is optimal with respect to the decisions of others. Bounded rationality modeling, for which there is a long history and extensive body of research, seeks to understand game outcomes where the capacity of agents to act as optimizers is limited, as would be the case in large-scale or complex environments. This talk presents two approaches to bounded rationality inspired by concepts in feedback control. The first is in the setting of learning in games, where agents utilize simple adaptive rules over the course of repeated interactions to adjust their decisions. We present an overview of the control theoretic concept of passivity, which captures the behavior of many learning rules considered in the learning in games literature. This model imposes an intuitive dynamic constraint on how decisions evolve in reaction to dynamic rewards. We present preliminary experimental results that examine the degree to which participant decisions are consistent with passivity modeling. The second is in the setting of partially observed stochastic games. We describe an alternative equilibrium concept, termed empirical evidence equilibria, where agents utilize reduced order models of both the environment and decision rules of other agents. We establish existence results for such equilibria and, in special settings, compare to Nash equilibria, correlated equilibria, and mean field games.
Bio: Jeff S. Shamma is with the University of Illinois at Urbana-Champaign where he is the Department Head of Industrial and Enterprise Systems Engineering (ISE) and Jerry S. Dobrovolny Chair in ISE. His prior academic appointments include faculty positions at the King Abdullah University of Science and Technology (KAUST) and Georgia Institute of Technology, where he was the Julian T. Hightower Chair in Systems and Controls. Jeff received a PhD in Systems Science and Engineering from MIT in 1988. He is a Fellow of IEEE and IFAC; a recipient of the IFAC High Impact Paper Award, AACC Donald P. Eckman Award, and NSF Young Investigator Award; and a past Distinguished Lecturer of the IEEE Control Systems Society. Jeff is currently serving as Editor-in-Chief for the IEEE Transactions on Control of Network Systems.