Mechanical and Aerospace Engineering Department
University of California - Los Angeles
Multiagent Repeated Games and convergence to Nash Equilibria
Consider a scenario in which multiple decision making agents repeatedly play a matrix game and adjust their strategies according to observations of each other's actions. The game is noncooperative in that each agent may have its own objective/utility function, and these objectives are not shared among agents. A central issue is whether agent strategies will converge to a Nash equilibrium. Prior work shows how convergence to a Nash equilibrium in this setting may or may not occur. This talk presetns new strategic update mechanisms that can lead to convergent behavior in previously nonconvergent cases, such as the Shapley and Jordan counterexamples, through the use of fundamental feedback control concepts.