Stochastic multi-agent systems raise the necessity to extend probabilistic model checking to the epistemic domain. Results in this direction have been achieved by epistemic extensions of Probabilistic Computation Tree Logic and related Probabilistic Interpreted Systems. The latter, however, suffer of an important limitation: they require the probabilities governing the system’s behaviour to be fully specified. A promising way to overcome this limitation is represented by imprecise probabilities. In this paper we introduce imprecise probabilistic interpreted systems and present a related logical language and model-checking procedures based on recent advances in the study of imprecise Markov processes.

Logic and Model Checking by Imprecise Probabilistic Interpreted Systems / A. Termine, A. Antonucci, G. Primiero, A. Facchini (LECTURE NOTES IN COMPUTER SCIENCE). - In: Multi-Agent Systems / [a cura di] A. Rosenfeld, N. Talmon. - Prima edizione. - Ebook. - [s.l] : Springer, 2021. - ISBN 978-3-030-82253-8. - pp. 211-227 (( Intervento presentato al 18. convegno European Conference on Multi-Agent Systems tenutosi a Jerusalem nel 2021 [10.1007/978-3-030-82254-5_13].

Logic and Model Checking by Imprecise Probabilistic Interpreted Systems

A. Termine
Primo
Writing – Original Draft Preparation
;
G. Primiero
Penultimo
Writing – Original Draft Preparation
;
2021

Abstract

Stochastic multi-agent systems raise the necessity to extend probabilistic model checking to the epistemic domain. Results in this direction have been achieved by epistemic extensions of Probabilistic Computation Tree Logic and related Probabilistic Interpreted Systems. The latter, however, suffer of an important limitation: they require the probabilities governing the system’s behaviour to be fully specified. A promising way to overcome this limitation is represented by imprecise probabilities. In this paper we introduce imprecise probabilistic interpreted systems and present a related logical language and model-checking procedures based on recent advances in the study of imprecise Markov processes.
Probabilistic Interpreted Systems; Imprecise Markov chains; Imprecise probabilities; Model checking
Settore M-FIL/02 - Logica e Filosofia della Scienza
Settore MAT/01 - Logica Matematica
Settore INF/01 - Informatica
Dipartimenti di Eccellenza 2018-2022 - Dipartimento di FILOSOFIA
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/868337
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