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• W3204262485 abstract "A tool, MIDES, for automatic learning of models and supervisors for discrete event systems is presented. The tool interfaces with a simulation of the target system to learn a behavioral model through interaction. There are several different algorithms to choose from depending on the intended outcome. Moreover, given a set of specifications, the tool learns a supervisor that can help ensure the controlled system guarantees the specifications. Furthermore, the state-space explosion problem is addressed by learning a modular supervisor. In this paper, we introduce the tool, its interfaces, and algorithms. We demonstrate the usefulness through several case studies." @default.
• W3204262485 created "2021-10-11" @default.
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• W3204262485 date "2021-08-23" @default.
• W3204262485 modified "2023-10-18" @default.
• W3204262485 title "MIDES: A Tool for Supervisor Synthesis via Active Learning" @default.
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• W3204262485 doi "https://doi.org/10.1109/case49439.2021.9551435" @default.
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