The model checking problem for multi-agent systems against Strategy Logic specifications is known to be non-elementary. On this logic several fragments have been defined to tackle this issue but at the expense of expressiveness. In this paper, we propose a three-valued semantics for Strategy Logic upon which we define an abstraction method. We show that the latter semantics is an approximation of the classic two-valued one for Strategy Logic. Furthermore, we extend MCMAS, an open-source model checker for multi-agent specifications, to incorporate our abstraction method and present some promising experimental results.

Scalable Verification of Strategy Logic through Three-Valued Abstraction / Belardinelli, Francesco; Ferrando, Angelo; Jamroga, Wojciech; Malvone, Vadim; Murano, Aniello. - In: IJCAI. - ISSN 1045-0823. - (2023), pp. 46-54. (Intervento presentato al convegno 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 tenutosi a Macao, PRC nel AUG 19-25, 2023) [10.24963/ijcai.2023/6].

Scalable Verification of Strategy Logic through Three-Valued Abstraction

Angelo Ferrando;
2023

Abstract

The model checking problem for multi-agent systems against Strategy Logic specifications is known to be non-elementary. On this logic several fragments have been defined to tackle this issue but at the expense of expressiveness. In this paper, we propose a three-valued semantics for Strategy Logic upon which we define an abstraction method. We show that the latter semantics is an approximation of the classic two-valued one for Strategy Logic. Furthermore, we extend MCMAS, an open-source model checker for multi-agent specifications, to incorporate our abstraction method and present some promising experimental results.
2023
32nd International Joint Conference on Artificial Intelligence, IJCAI 2023
Macao, PRC
AUG 19-25, 2023
46
54
Belardinelli, Francesco; Ferrando, Angelo; Jamroga, Wojciech; Malvone, Vadim; Murano, Aniello
Scalable Verification of Strategy Logic through Three-Valued Abstraction / Belardinelli, Francesco; Ferrando, Angelo; Jamroga, Wojciech; Malvone, Vadim; Murano, Aniello. - In: IJCAI. - ISSN 1045-0823. - (2023), pp. 46-54. (Intervento presentato al convegno 32nd International Joint Conference on Artificial Intelligence, IJCAI 2023 tenutosi a Macao, PRC nel AUG 19-25, 2023) [10.24963/ijcai.2023/6].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1331844
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