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Finite LTL Synthesis with Environment Assumptions and Quality Measures

Alberto Camacho 1 Meghyn Bienvenu 2 Sheila Mcilraith 1
2 GRAPHIK - Graphs for Inferences on Knowledge
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier, CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In this paper, we investigate the problem of synthesizing strategies for linear temporal logic (LTL) specifications that are interpreted over finite traces - a problem that is central to the automated construction of controllers, robot programs, and business processes. We study a natural variant of the finite LTL synthesis problem in which strategy guarantees are predicated on specified environment behavior. We further explore a quantitative extension of LTL that supports specification of quality measures, utilizing it to synthesize high-quality strategies. We propose new notions of optimality and associated algorithms that yield strategies that best satisfy specified quality measures. Our algorithms utilize an automata-game approach, positioning them well for future implementation via existing state-of-the-art techniques.
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Submitted on : Wednesday, October 10, 2018 - 4:26:34 PM
Last modification on : Tuesday, March 9, 2021 - 11:55:03 AM

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  • HAL Id : lirmm-01892548, version 1
  • ARXIV : 1808.10831

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Alberto Camacho, Meghyn Bienvenu, Sheila Mcilraith. Finite LTL Synthesis with Environment Assumptions and Quality Measures. 16th International Conference on Principles of Knowledge Representation and Reasoning (KR 2018), Oct 2018, Tempe, United States. pp.454-463. ⟨lirmm-01892548⟩

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