Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning Yiqin Y ang

Moreover, we extend ICQ to multi-agent tasks by decomposing the joint-policy under the implicit constraint. Experimental results demonstrate that the extrapolation error is successfully controlled within a reasonable range and insensitive to the number of agents.