We consider an agent acting to fulfil tasks in a nondeterministic environment. When a strategy that fulfills the task regardless of how the environment acts does not exist, the agent should at least avoid adopting strategies that prevent from fulfilling its task. Best-effort synthesis captures this intuition. In this paper, we devise and compare various symbolic approaches for best-effort synthesis in Linear Temporal Logic on finite traces (\LTLf). These approaches are based on the same basic components, however they change in how these components are combined, and this has a significant impact on the performance of the approaches as confirmed by our empirical evaluations.

Symbolic LTLf Best-Effort Synthesis / De Giacomo, Giuseppe; Parretti, Gianmarco; Zhu, Shufang. - 14282:(2023), pp. 228-243. ( 20th European Conference on Multi-Agent Systems, EUMAS 2023 Napoli ) [10.1007/978-3-031-43264-4_15].

Symbolic LTLf Best-Effort Synthesis

Giuseppe De Giacomo;Gianmarco Parretti
;
Shufang Zhu
2023

Abstract

We consider an agent acting to fulfil tasks in a nondeterministic environment. When a strategy that fulfills the task regardless of how the environment acts does not exist, the agent should at least avoid adopting strategies that prevent from fulfilling its task. Best-effort synthesis captures this intuition. In this paper, we devise and compare various symbolic approaches for best-effort synthesis in Linear Temporal Logic on finite traces (\LTLf). These approaches are based on the same basic components, however they change in how these components are combined, and this has a significant impact on the performance of the approaches as confirmed by our empirical evaluations.
2023
20th European Conference on Multi-Agent Systems, EUMAS 2023
Linear Temporal Logic on Finite Traces; Best-Effort Synthesis; Symbolic Techniques
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Symbolic LTLf Best-Effort Synthesis / De Giacomo, Giuseppe; Parretti, Gianmarco; Zhu, Shufang. - 14282:(2023), pp. 228-243. ( 20th European Conference on Multi-Agent Systems, EUMAS 2023 Napoli ) [10.1007/978-3-031-43264-4_15].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1690354
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