Presentation | 2009-01-29 Reinforcement Learning of Optimal Supervisor based on the Worst-Case Behavior Kouji KAJIWARA, Tatsushi YAMASAKI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Ramadge and Wonham proposed the supervisory control, which is a framework for logical control of discrete event systems. However, in the ordinary supervisory control, the costs for occurence and disabling of events have not been considered. This paper proposes a synthesis method of the supervisor based on the worst-case behavior of discrete event systems. We introduce the new value functions for the assigned control patterns. The new value functions are not based on the expected total rewards, but based on the most undesirable event ocurrence in the assigned control pattern. In the proposed method, the supervisor learns how to assign the control pattern based on reinforcement learning so as to maximize the value functions. We show the efficiency of the proposed method by computer simulation. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Discrete event systems / supervisory control / reinforcement learning |
Paper # | CST2008-49 |
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Committee | CST |
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Conference Date | 2009/1/22(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Concurrent System Technology (CST) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Reinforcement Learning of Optimal Supervisor based on the Worst-Case Behavior |
Sub Title (in English) | |
Keyword(1) | Discrete event systems |
Keyword(2) | supervisory control |
Keyword(3) | reinforcement learning |
1st Author's Name | Kouji KAJIWARA |
1st Author's Affiliation | Faculty of Engineering, Setsunan University() |
2nd Author's Name | Tatsushi YAMASAKI |
2nd Author's Affiliation | Faculty of Engineering, Setsunan University |
Date | 2009-01-29 |
Paper # | CST2008-49 |
Volume (vol) | vol.108 |
Number (no) | 415 |
Page | pp.pp.- |
#Pages | 6 |
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