Decentralized multi-agent reinforcement learning based on best-response policies

Introduction: Multi-agent systems are an interdisciplinary research field that describes the concept of multiple decisive individuals interacting with a usually partially observable environment. Given the recent advances in single-agent reinforcement learning, multi-agent reinforcement learning (RL)...

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Vydáno v:	Frontiers in robotics and AI Ročník 11; s. 1229026
Hlavní autoři:	Gabler, Volker, Wollherr, Dirk
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland Frontiers Media S.A 16.04.2024
Témata:	actor–critic algorithm deep learning, artificial intelligence game theory multi-agent multi-agent reinforcement learning Robotics and AI Stackelberg deep learning, artificial intelligence multi-agent reinforcement learning Stackelberg multi-agent reinforcement leaning game theory decentralized learning schemes actor–critic algorithm
ISSN:	2296-9144, 2296-9144
On-line přístup:	Získat plný text
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