Strategies for Energy-Aware Multi-agent Continuous Cooperative Patrolling Problems Subject to Requirements

Lingying Wu, Toshiharu Sugawara

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

Abstract

This paper proposes a method of autonomous strategy learning for multiple cooperative agents integrated with a series of behavioral strategies aiming at reduction of energy cost on the premise of satisfying quality requirements in continuous patrolling problems. We improved our algorithm of requirement estimation to avoid concentration of agents since they are given the knowledge of the work environment in advance. The experimental results show that our proposal enables the agents to learn to select appropriate behavioral planning strategies according to performance efficiency and energy cost, and to individually estimate whether the given requirement is reached and modify their action plans to save energy. Furthermore, agents with the new requirement estimation method could achieve fair patrolling by introducing local observations.

Original languageEnglish
Title of host publicationPRIMA 2019
Subtitle of host publicationPrinciples and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings
EditorsMatteo Baldoni, Mehdi Dastani, Beishui Liao, Yuko Sakurai, Rym Zalila Wenkstern
PublisherSpringer
Pages585-593
Number of pages9
ISBN (Print)9783030337919
DOIs
Publication statusPublished - 2019
Event22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019 - Turin, Italy
Duration: 2019 Oct 282019 Oct 31

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11873 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2019
CountryItaly
CityTurin
Period19/10/2819/10/31

Keywords

  • Continuous patrolling
  • Cooperation
  • Energy efficiency
  • Learning
  • Multi-agent systems

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Wu, L., & Sugawara, T. (2019). Strategies for Energy-Aware Multi-agent Continuous Cooperative Patrolling Problems Subject to Requirements. In M. Baldoni, M. Dastani, B. Liao, Y. Sakurai, & R. Zalila Wenkstern (Eds.), PRIMA 2019: Principles and Practice of Multi-Agent Systems - 22nd International Conference, Proceedings (pp. 585-593). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11873 LNAI). Springer. https://doi.org/10.1007/978-3-030-33792-6_44