Multi-Agent Coordination in Open Environments

This paper proposes a new approach to multi-agent systems leveraging from recent advances in networking and reinforcement learning to scale up teamwork based on joint intentions. In this approach, teamwork is subsumed by the coordination of learning agents. The intuition behind this approach is that successful coordination at the global level generates opportunities for teamwork interactions at the local level and vice versa. This unique approach scales up model-based teamwork theory with an adaptive approach to coordination. Some preliminary results are reported using a novel coordination evaluation.