Presentation 2014-11-21
On optimal LLP supervisory control of discrete event systems based on reinforcement learning
Hijiri UMEMOTO, Tatsushi YAMASAKI,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) LLP (Limited Lookahead Policy) supervisory control has been proposed to control the logical behavior of large scale or time varying discrete event systems. In this paper, we propose an optimal LLP supervisory control method considering the costs of occurrence and disabling events for the system composed of plural subsystems. In the proposed method, each subsystem learns the evaluation for control patterns based on reinforcement learning. The LLP supervisor selects the optimal control pattern based on the value function within the given specifications.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) supervisory control / discrete event system / limited lookahead policy / optimal control / reinforcement learning
Paper # CAS2014-102,MSS2014-66
Date of Issue

Conference Information
Committee MSS
Conference Date 2014/11/13(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Mathematical Systems Science and its applications(MSS)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) On optimal LLP supervisory control of discrete event systems based on reinforcement learning
Sub Title (in English)
Keyword(1) supervisory control
Keyword(2) discrete event system
Keyword(3) limited lookahead policy
Keyword(4) optimal control
Keyword(5) reinforcement learning
1st Author's Name Hijiri UMEMOTO
1st Author's Affiliation Graduate School of Science and Technology, Setsunan University()
2nd Author's Name Tatsushi YAMASAKI
2nd Author's Affiliation Faculty of Science and Technology, Setsunan University
Date 2014-11-21
Paper # CAS2014-102,MSS2014-66
Volume (vol) vol.114
Number (no) 313
Page pp.pp.-
#Pages 6
Date of Issue