Presentation | 2014-11-21 On optimal LLP supervisory control of discrete event systems based on reinforcement learning Hijiri UMEMOTO, Tatsushi YAMASAKI, |
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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 |
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Committee | MSS |
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Conference Date | 2014/11/13(1days) |
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Registration To | Mathematical Systems Science and its applications(MSS) |
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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 |
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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 |
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