Elevator Group Control Using Multiagent Task-Oriented Reinforcement Learning

• Kamal M. A. S.

  Graduate School of Information Science and Electrical Engineering, Kyushu University

• Murata Junichi

  Graduate School of Information Science and Electrical Engineering, Kyushu University

• Hirasawa Kotaro

  Graduate School of Information, Production and Systems, Waseda University

抄録

In this paper, a reinforcement learning method is proposed that optimizes passenger service in elevator group systems. Task-oriented reinforcement learning using multiple agents is applied in the control system in allocating immediate landing calls to the elevators and operating them intelligently in attaining better service in this stochastic dynamic domain. The proposed system shows better adaptive performance in different traffic profiles with faster convergence compared to the other learning elevator group control system.

収録刊行物

• 電気学会論文誌Ｃ（電子・情報・システム部門誌）

  電気学会論文誌Ｃ（電子・情報・システム部門誌） 125 (7), 1140-1146, 2005

  一般社団法人 電気学会

キーワード

• elevator group control
• task-oriented reinforcement learning
• multiagent systems

詳細情報

• CRID: 1390282679581139712
• NII論文ID: 10016466691
• NII書誌ID: AN10065950
• DOI: 10.1541/ieejeiss.125.1140
• ISSN: 13488155
• ISSN: 03854221
• NDL書誌ID: 7415242
• Web Site: https://ndlsearch.ndl.go.jp/books/R000000004-I7415242
• Web Site: http://www.jstage.jst.go.jp/article/ieejeiss/125/7/125_7_1140/_pdf
• 本文言語コード: en
• データソース種別:
  • JaLC
  • NDL
  • Crossref
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可