From Agents to Robots: A Training and Evaluation Platform for Multi-robot Reinforcement Learning

Multi-robot reinforcement learning (MRRL) is a promising approach to solving cooperation problems and has been widely adopted in many applications. In the past decades, researchers have proposed various approaches to improve the efficiency of MRRL. However, most of them are trained and evaluated onl...

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Vydané v:	Proceedings - International Conference on Parallel and Distributed Systems s. 593 - 600
Hlavní autori:	Liang, Zhiuxan, Cao, Jiannong, Jiang, Shan, Saxena, Divya, Cao, Rui, Xu, Huafeng
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 10.10.2024
Predmet:	Autonomous vehicles Benchmark testing Codes Faces Multi-robot Reinforcement Learning Multi-robot Simulator Multi-Robot System Multi-robot systems Performance evaluation Reinforcement learning Robots Training
ISSN:	2690-5965
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