Finite-trace and generalized-reactivity specifications in temporal synthesis

Linear Temporal Logic (LTL) synthesis aims at automatically synthesizing a program that complies with desired properties expressed in LTL. Unfortunately it has been proved to be too difficult computationally to perform full LTL synthesis. There have been two success stories with LTL synthesis, both...

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Автори: De Giacomo, G, Di Stasio, A, Tabajara, LM, Vardi, MY, Zhu, S
Формат: Journal article
Мова:English
Опубліковано: Springer 2023
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author De Giacomo, G
Di Stasio, A
Tabajara, LM
Vardi, MY
Zhu, S
author_facet De Giacomo, G
Di Stasio, A
Tabajara, LM
Vardi, MY
Zhu, S
author_sort De Giacomo, G
collection OXFORD
description Linear Temporal Logic (LTL) synthesis aims at automatically synthesizing a program that complies with desired properties expressed in LTL. Unfortunately it has been proved to be too difficult computationally to perform full LTL synthesis. There have been two success stories with LTL synthesis, both having to do with the form of the specification. The first is the GR(1) approach: use safety conditions to determine the possible transitions in a game between the environment and the agent, plus one powerful notion of fairness, Generalized Reactivity(1), or GR(1). The second, inspired by AI planning, is focusing on finite-trace temporal synthesis, with LTLf (LTL on finite traces) as the specification language. In this paper we take these two lines of work and bring them together. We first study the case in which we have an LTLf agent goal and a GR(1) environment specification. We then add to the framework safety conditions for both the environment and the agent, obtaining a highly expressive yet still scalable form of LTL synthesis.
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spelling oxford-uuid:db7f02cd-0eff-4ec8-bd0e-9cd00b17fdaa2024-05-13T15:28:29ZFinite-trace and generalized-reactivity specifications in temporal synthesisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:db7f02cd-0eff-4ec8-bd0e-9cd00b17fdaaEnglishSymplectic ElementsSpringer2023De Giacomo, GDi Stasio, ATabajara, LMVardi, MYZhu, SLinear Temporal Logic (LTL) synthesis aims at automatically synthesizing a program that complies with desired properties expressed in LTL. Unfortunately it has been proved to be too difficult computationally to perform full LTL synthesis. There have been two success stories with LTL synthesis, both having to do with the form of the specification. The first is the GR(1) approach: use safety conditions to determine the possible transitions in a game between the environment and the agent, plus one powerful notion of fairness, Generalized Reactivity(1), or GR(1). The second, inspired by AI planning, is focusing on finite-trace temporal synthesis, with LTLf (LTL on finite traces) as the specification language. In this paper we take these two lines of work and bring them together. We first study the case in which we have an LTLf agent goal and a GR(1) environment specification. We then add to the framework safety conditions for both the environment and the agent, obtaining a highly expressive yet still scalable form of LTL synthesis.
spellingShingle De Giacomo, G
Di Stasio, A
Tabajara, LM
Vardi, MY
Zhu, S
Finite-trace and generalized-reactivity specifications in temporal synthesis
title Finite-trace and generalized-reactivity specifications in temporal synthesis
title_full Finite-trace and generalized-reactivity specifications in temporal synthesis
title_fullStr Finite-trace and generalized-reactivity specifications in temporal synthesis
title_full_unstemmed Finite-trace and generalized-reactivity specifications in temporal synthesis
title_short Finite-trace and generalized-reactivity specifications in temporal synthesis
title_sort finite trace and generalized reactivity specifications in temporal synthesis
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