Yang, Erfu and Gu, Dongbing (2009) 'Multi-robot systems with agent-based reinforcement learning: evolution, opportunities and challenges.' International Journal of Modelling, Identification and Control, 6 (4). p. 271. ISSN 1746-6172

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Abstract

Multi-agent reinforcement learning for multi-robot systems is a challenging issue in both robotics and artificial intelligence. With the ever increasing interests in theoretical researches and practical applications, currently there have been a lot of efforts towards providing good solutions to this challenge. However, there are still many difficulties in scaling up multi-agent reinforcement learning to multi-robot systems. This paper presents a survey on the evolution, opportunities and challenges of applying agent-based reinforcement learning to multi-robot systems. After reviewing some important advances in this field, some challenging problems and promising research directions are focused on. A concluding remark is made from the perspectives of the authors. Copyright © 2009, Inderscience Publishers.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:	Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor:	Elements
Depositing User:	Elements
Date Deposited:	20 Oct 2012 09:07
Last Modified:	15 Jan 2022 00:44
URI:	http://repository.essex.ac.uk/id/eprint/4042

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