Exploiting factored representations for decentralized execution in multiagent teams

In many cooperative multiagent domains, there exist some states in which the agents can act independently and others in which they need to coordinate with their teammates. In this paper, we explore how factored representations of state can be used to generate factored policies that can, with minimal communication, be executed distributedly by a multiagent team. The factored policies indicate those portions of the state where no coordination is necessary, automatically alert the agents when they reach a state in which they do need to coordinate, and determine what the agents should communicate in order to achieve this coordination. We evaluate the success of our approach experimentally by comparing the amount of communication needed by a team executing a factored policy to a team that needs to communicate in every timestep.