A survey on multiagent reinforcement learning towards multi-robot systems

Erfu Yang, Dongbing Gu

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

11 Citations (Scopus)

Abstract

Multiagent reinforcement learning for multirobot systems is a challenging issue in both robotics and artificial intelligence. With the ever increasing interests in theoretical research and practical applications, currently there have been a lot of efforts towards providing some solutions to this challenge. However, there are still many difficulties in scaling up multiagent reinforcement learning to multi-robot systems. The main objective of this paper is to provide a survey on multiagent reinforcement learning in multi-robot systems, based on the literature the authors collected. After reviewing some important advances in this field, some challenging problems are analyzed. A concluding remark is made from the perspectives of the authors.

Original languageEnglish
Title of host publicationIEEE 2005 Symposium on Computational Intelligence and Games, CIG'05
PublisherIEEE
Pages292-299
Number of pages8
Publication statusPublished - 1 Dec 2005
Event2005 IEEE Symposium on Computational Intelligence and Games, CIG'05 - Colchester, Essex, United Kingdom
Duration: 4 Apr 20056 Apr 2005

Conference

Conference2005 IEEE Symposium on Computational Intelligence and Games, CIG'05
CountryUnited Kingdom
CityColchester, Essex
Period4/04/056/04/05

Keywords

  • multi-robot systems
  • artificial Intelligence
  • multiagent reinforcement learning

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