Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
Abstract. We consider Reinforcement Learning for average reward zerosum stochastic games. We present and analyze two algorithms. The first is based on relative Q-learning and the ...
This paper treats the problem of distributed planning in general-sum stochastic games with communication when the model is known. Our main contribution is a novel, game theoretic ...
This paper studies a stochastic game theoretic approach to security and intrusion detection in communication and computer networks. Specifically, an Attacker and a Defender take pa...
We define stochastic timed games, which extend two-player timed games with probabilities (following a recent approach by Baier et al), and which extend in a natural way continuous-...