Effective area partitioning in a multi-agent patrolling domain for better efficiency

Katsuya Hattori, Toshiharu Sugawara

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

Abstract

This study proposes a cooperative method for a multi-agent continuous cooperative patrolling problem by partitioning the environment into a number of subareas so that the workload is balanced among multiple agents by allocating subareas to individual agents. Owing to the advancement in robotics and information technology over the years, robots are being utilized in many applications. As environments are usually vast and complicated, a single robot (agent) cannot supervise the entire work. Thus, cooperative work by multiple agents, even though complicated, is indispensable. This study focuses on cooperation in a bottom-up manner by fairly partitioning the environment into subareas, and employing each agent to work on them as its responsibility. However, as the agents do not monitor the entire environment, the decentralized control may generate unreasonable shapes of subareas; the area are often unnecessarily divided into fragmented enclaves, resulting in inefficiency. Our proposed method reduced the number of small and isolated enclaves by negotiation. Our experimental results indicated that our method eliminated the minute/unnecessary fragmented enclaves and improved performance when compared with the results obtained by conventional methods.

Original languageEnglish
Title of host publicationICAART 2021 - Proceedings of the 13th International Conference on Agents and Artificial Intelligence
EditorsAna Paula Rocha, Luc Steels, Jaap van den Herik
PublisherSciTePress
Pages281-288
Number of pages8
ISBN (Electronic)9789897584848
Publication statusPublished - 2021
Event13th International Conference on Agents and Artificial Intelligence, ICAART 2021 - Virtual, Online
Duration: 2021 Feb 42021 Feb 6

Publication series

NameICAART 2021 - Proceedings of the 13th International Conference on Agents and Artificial Intelligence
Volume1

Conference

Conference13th International Conference on Agents and Artificial Intelligence, ICAART 2021
CityVirtual, Online
Period21/2/421/2/6

Keywords

  • Cooperative agent
  • Division of labor
  • Multi-agent system
  • Negotiation
  • Patrolling problem

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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