Yang, E and Gu, D (2009) 'Multi-robot systems with agent-based reinforcement learning: Evolution, opportunities and challenges.' International Journal of Modelling, Identification and Control, 6 (4). 271 - 286. ISSN 1746-6172

Full text not available from this repository.

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 > Computer Science and Electronic Engineering, School of
Depositing User:	Clare Chatfield
Date Deposited:	20 Oct 2012 09:07
Last Modified:	23 Jan 2019 00:16
URI:	http://repository.essex.ac.uk/id/eprint/4042

Actions (login required)

View Item