Reaching Consensus in Cooperative Multi-Agent Reinforcement Learning with Goal Imagination

arXiv:2403.03172v1 Announce Type: cross
Abstract: Reaching consensus is key to multi-agent coordination. To accomplish a cooperative task, agents need to coherently select optimal joint actions to maximize the team reward. However, current cooperative multi-agent reinforcement learning (MARL) methods usually do not explicitly take consensus into consideration, which may cause miscoordination problem. In this paper, we propose a model-based consensus mechanism to explicitly coordinate multiple agents. The proposed Multi-agent Goal Imagination (MAGI) framework guides agents to reach consensus with an Imagined …

abstract agent agents arxiv consensus cs.ai cs.lg current imagination key multi-agent reinforcement reinforcement learning team type