Weighted QMIX: Expanding monotonic value function factorisation for deep multi−agent reinforcement learning

Weighted QMIX: Expanding monotonic value function factorisation for deep multi−agent reinforcement learning

QMIX is a popular Q-learning algorithm for cooperative MARL in the centralised training and decentralised execution paradigm. In order to enable easy decentralisation, QMIX restricts the joint action Q-values it can represent to be a monotonic mixing of each agent’s utilities. However, this restrict...

書誌詳細
主要な著者:	Rashid, T, Farquhar, G, Peng, B, Whiteson, S
フォーマット:	Conference item
言語:	English
出版事項:	NeurIPS 2020

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