Multi-robot systems with agent-based reinforcement learning : evolution, opportunities and challenges

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). pp. 271-286. ISSN 1746-6172 (https://doi.org/10.1504/IJMIC.2009.024735)

Full text not available in this repository.Request a copy

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.

ORCID iDs

Yang, Erfu ORCID logoORCID: https://orcid.org/0000-0003-1813-5950 and Gu, Dongbing;
CORE (COnnecting REpositories)