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Communication Dans Un Congrès Année : 2020

Expressiveness and Conciseness of Timed Automata for the Verification of Stochastic Models

Résumé

A central task in partially observed controllable system is to detect or prevent the occurrence of certain events called faults. Systems for which one can design a controller avoiding the faults are called actively safe. Otherwise, one may require that a fault is eventually detected, which is the task of diagnosis. Systems for which one can design a controller detecting the faults are called actively diagnosable. An intermediate requirement is prediction, which consists in determining that a fault will occur whatever the future behaviour of the system. When a system is not predictable, one may be interested in designing a controller to make it so. Here we study the latter problem, called active prediction, and its associated property, active predictability. In other words, we investigate how to determine whether or not a system enjoys the active predictability property, i.e., there exists an active predictor for the system. Our contributions are threefold. From a semantical point of view, we refine the notion of predictability by adding two quantitative requirements: the minimal and maximal delay before the occurence of the fault, and we characterize the requirements fulfilled by a controller that performs predictions. Then we show that active predictability is EXPTIME-complete where the upper bound is obtained via a game-based approach. Finally we establish that active predictability is equivalent to active safety when the maximal delay is beyond a threshold depending on the size of the system, and we show that this threshold is accurate by exhibiting a family of systems fulfilling active predictability but not active safety.

Dates et versions

hal-04390304 , version 1 (12-01-2024)

Identifiants

Citer

Susanna Donatelli, Serge Haddad. Expressiveness and Conciseness of Timed Automata for the Verification of Stochastic Models. Language and Automata Theory and Applications. LATA 2020., 2020, Milan, Italy. pp.170-183, ⟨10.1007/978-3-030-40608-0_11⟩. ⟨hal-04390304⟩
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