A leader-following paradigm based deep reinforcement learning method for multi-agent cooperation games

DOI10.1016/j.neunet.2022.09.012zbMath1525.91030OpenAlexW4297106287WikidataQ114950018 ScholiaQ114950018MaRDI QIDQ6077668

Dou An, Qingyu Yang, Feiye Zhang

Publication date: 18 October 2023

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2022.09.012

zbMATH Keywords

cooperative gamesmulti-agent systemsdeep reinforcement learningcentralized training with decentralized execution

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Cooperative games (91A12) Hierarchical systems (93A13) Multi-agent systems (93A16)

Cites Work

• Improving coordination in small-scale multi-agent deep reinforcement learning through memory-driven communication
• A Concise Introduction to Decentralized POMDPs

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