Emerging coordination in infinite team Markov games
Francisco S. Melo, Isabel Ribeiro · 2008
In this paper we address the problem of coordination in multi-agent sequential decision problems with infinite state-spaces. We adopt a game theoretic formalism to describe the interaction of the multiple decision-makers and propose the novel approximate biased adaptive play algorithm. This al-gorithm is an extension of biased adaptive play to team Mar-kov games defined over infinite state-spaces. We establish our method to coordinate with probability 1 in the optimal strategy and discuss how this methodology can be combined with approximate learning architectures. We conclude with two simple examples of application of our algorithm.