This paper discusses the infinite horizon stochastic Nash games with state-dependent noise. After establishing the asymptotic structure along with the positive semidefiniteness for...
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
We define the class of games called simulation-based games, in which the payoffs are available as an output of an oracle (simulator), rather than specified analytically or using a...
Abstract- Monte Carlo simulations have been successfully used in classic turn–based games such as backgammon, bridge, poker, and Scrabble. In this paper, we apply the ideas to th...
We propose axiomatizing some stochastic games, in a continuous state space setting, using continuous belief functions, resp. plausibilities, instead of measures. Then, stochastic g...