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Artificial Intelligence Review

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24.11.2020

A survey on multi-agent deep reinforcement learning: from the perspective of challenges and applications

verfasst von: Wei Du, Shifei Ding

Erschienen in: Artificial Intelligence Review | Ausgabe 5/2021

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Abstract

Deep reinforcement learning has proved to be a fruitful method in various tasks in the field of artificial intelligence during the last several years. Recent works have focused on deep reinforcement learning beyond single-agent scenarios, with more consideration of multi-agent settings. The main goal of this paper is to provide a detailed and systematic overview of multi-agent deep reinforcement learning methods in views of challenges and applications. Specifically, the preliminary knowledge is introduced first for a better understanding of this field. Then, a taxonomy of challenges is proposed and the corresponding structures and representative methods are introduced. Finally, some applications and interesting future opportunities for multi-agent deep reinforcement learning are given.

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Titel: A survey on multi-agent deep reinforcement learning: from the perspective of challenges and applications
verfasst von: Wei Du
Shifei Ding
Publikationsdatum: 24.11.2020
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 5/2021
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-020-09938-y

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