Presentation 2022-09-16
マルチエージェント協調巡回問題におけるエネルギー消費抑制手法の提案
Kohei Matsumoto, Keisuke Yoneda, Toshiharu Sugawara,
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Abstract(in English) In this paper, we propose a method for autonomously reducing energy consumption while satisfying quality requirements in the multi-agent cooperative patrolling problem (MACPP). Although it is important to execute tasks efficiently, executing tasks beyond the required quality may result in unnecessary energy consumption. In this study, we extend an existing method to reduce energy consumption by estimating that each agent satisfies a given quality requirement, and adjusting the estimation to reduce unnecessary actions. Evaluation experiments show that the proposed method is more effective than existing methods by introducing parameters that adaptively adjust energy-saving behaviors, thereby reducing energy consumption at the same time as satisfying the required quality.
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Paper # AI2022-31
Date of Issue 2022-09-08 (AI)

Conference Information
Committee AI
Conference Date 2022/9/15(2days)
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Chair Yuichi Sei(Univ. of Electro-Comm.)
Vice Chair Yuko Sakurai(AIST) / Tadachika Ozono(Nagoya Inst. of Tech.)
Secretary Yuko Sakurai(Tokyo Univ. of Agriculture and Technology) / Tadachika Ozono(Toho Univ.)
Assistant Kazutaka Matsuzaki(Chuo Univ.)

Paper Information
Registration To Technical Committee on Artificial Intelligence and Knowledge-Based Processing
Language JPN-ONLY
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1st Author's Name Kohei Matsumoto
1st Author's Affiliation Waseda University(Waseda Univ.)
2nd Author's Name Keisuke Yoneda
2nd Author's Affiliation Waseda University(Waseda Univ.)
3rd Author's Name Toshiharu Sugawara
3rd Author's Affiliation Waseda University(Waseda Univ.)
Date 2022-09-16
Paper # AI2022-31
Volume (vol) vol.122
Number (no) AI-186
Page pp.pp.73-78(AI),
#Pages 6
Date of Issue 2022-09-08 (AI)