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 factorisation




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.



SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning

Neural Information Processing Systems

V alue factorisation is a useful technique for multi-agent reinforcement learning (MARL) in global reward game, however, its underlying mechanism is not yet fully understood. This paper studies a theoretical framework for value factorisation with interpretability via Shapley value theory.





SHAQ: Incorporating Shapley Value Theory into Multi-Agent Q-Learning

Neural Information Processing Systems

V alue factorisation is a useful technique for multi-agent reinforcement learning (MARL) in global reward game, however, its underlying mechanism is not yet fully understood. This paper studies a theoretical framework for value factorisation with interpretability via Shapley value theory.