FACMAC: FactoredMulti-AgentCentralised PolicyGradients

Neural Information Processing Systems 

However, FACMAClearnsacentralised butfactored critic,which combines per-agent utilities into the joint action-value function via a non-linear monotonic function, as inQMIX, apopular multi-agentQ-learning algorithm. However,unlikeQMIX, there are no inherent constraints on factoring the critic. We thus also employ a nonmonotonic factorisation and empirically demonstrate that its increased representational capacity allows it to solve some tasks that cannot be solved with monolithic, ormonotonically factored critics.

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