Reducing the Learning Time of Reinforcement Learning for the Supervisory Control of Discrete Event Systems

Reinforcement learning (RL) can obtain the supervisory controller for discrete-event systems modeled by finite automata and temporal logic. The published methods often have two limitations. First, a large number of training data are required to learn the RL controller. Second, the RL algorithms do n...

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Opis bibliograficzny

Główni autorzy:	Junjun Yang, Kaige Tan, Lei Feng, Ahmed M. El-Sherbeeny, Zhiwu Li
Format:	Artigo
Język:	Inglês
Wydane:	IEEE 2023-01-01
Seria:	IEEE Access
Hasła przedmiotowe:	Discrete event system linear temporal logic supervisory control theory reinforcement learning
Dostęp online:	https://ieeexplore.ieee.org/document/10149832/
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