Learning multi-agent strategies in multi-stage collaborative games

Abstract

An alternative approach to learning decision strategies in multi-state multiple agent systems is presented here. The method, which uses a game theoretic construction which is model free and does not rely on direct communication between the agents in the system. Limited experiments show that the method can find Nash equilibrium point for 3 player multi-stage game and converges more quickly than a comparable co-evolution method.