Weighted and Branching Bisimilarities from Generalized Open Maps
Dubut J, Wißmann T (2023)
Publication Type: Conference contribution
Publication year: 2023
Journal
Publisher: Springer Science and Business Media Deutschland GmbH
Book Volume: 13992 LNCS
Pages Range: 308-327
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Paris
ISBN: 9783031308284
DOI: 10.1007/978-3-031-30829-1_15
Abstract
In the open map approach to bisimilarity, the paths and their runs in a given state-based system are the first-class citizens, and bisimilarity becomes a derived notion. While open maps were successfully used to model bisimilarity in non-deterministic systems, the approach fails to describe quantitative system equivalences such as probabilistic bisimilarity. In the present work, we see that this is indeed impossible and we thus generalize the notion of open maps to also accommodate weighted and probabilistic bisimilarity. Also, extending the notions of strong path and path bisimulations into this new framework, we show that branching bisimilarity can be captured by this extended theory and that it can be viewed as the history preserving restriction of weak bisimilarity.
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APA:
Dubut, J., & Wißmann, T. (2023). Weighted and Branching Bisimilarities from Generalized Open Maps. In Orna Kupferman, Pawel Sobocinski (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 308-327). Paris, FR: Springer Science and Business Media Deutschland GmbH.
MLA:
Dubut, Jérémy, and Thorsten Wißmann. "Weighted and Branching Bisimilarities from Generalized Open Maps." Proceedings of the 26th International Conference on Foundations of Software Science and Computational Structures, FOSSACS 2023, held as part of the 26th European Joint Conferences on Theory and Practice of Software, ETAPS 2023, Paris Ed. Orna Kupferman, Pawel Sobocinski, Springer Science and Business Media Deutschland GmbH, 2023. 308-327.
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