Elevator group supervisory control system using GNP with reinforcement learning based on normalized information

Jin Zhou, Kotaro Hirasawa, Jinglu Hu, Sandor Markon

Research output: Contribution to conferencePaper

Abstract

Since Genetic Network Programming (GNP) has been proposed as a new method of evolutionary computation, many studies have been done to its applications which cover not only virtual world problems but also real world systems like Elevator Group Supervisory Control System (EGSCS). In this paper, Reinforcement Learning is introduced to study its applicability and availability in the EGSCS based on the GNP structure with hall call assignment part embedded.

Original languageEnglish
Pages74-79
Number of pages6
Publication statusPublished - 2005 Dec 1
EventSICE Annual Conference 2005 - Okayama, Japan
Duration: 2005 Aug 82005 Aug 10

Conference

ConferenceSICE Annual Conference 2005
CountryJapan
CityOkayama
Period05/8/805/8/10

Keywords

  • Elevator Group Supervisory Control System (EGSCS)
  • Genetic Network Programming (GNP)
  • Reinforcement Learning (RL)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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    Zhou, J., Hirasawa, K., Hu, J., & Markon, S. (2005). Elevator group supervisory control system using GNP with reinforcement learning based on normalized information. 74-79. Paper presented at SICE Annual Conference 2005, Okayama, Japan.