Computing Equilibria with Two-Player Zero-Sum Continuous Stochastic Games with Switching Controller

Guido Bonomi, Nicola Gatti, Fabio Panozzo, Marcello Restelli

Abstract: Equilibrium computation with continuous games is currently a challenging open task in artificial intelligence. In this paper, we design an iterative algorithm that finds an ε-approximate Markov perfect equilibrium with two-player zero-sum continuous stochastic games with switching controller. When the game is polynomial (i.e., utility and state transitions are polynomial functions), our algorithm converges to ε