FACMAC: Factored Multi-Agent Centralised Policy Gradients Bei Peng University of Liverpool T abish Rashid University of Oxford Christian A. Schroeder de Witt

Neural Information Processing Systems 

However, unlike QMIX, 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, or monotonically factored critics.

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