Elevator Group Control Using Multiagent Task-Oriented Reinforcement Learning

M. A.S. Kamal, Junichi Murata, Kotaro Hirasawa

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1140-1146
Number of pages7
JournalIEEJ Transactions on Electronics, Information and Systems
Volume125
Issue number7
DOIs
Publication statusPublished - Jan 1 2005

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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