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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Bibliographic Details

Published in:	Frontiers in robotics and AI Vol. 11; p. 1229026
Main Authors:	Gabler, Volker, Wollherr, Dirk
Format:	Journal Article
Language:	English
Published:	Switzerland Frontiers Media S.A 16.04.2024
Subjects:	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
Online Access:	Get full text
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