Characterising probabilistic processes logically

Yuxin Deng; Rob Van Glabbeek

doi:10.1007/978-3-642-16242-8-20

Characterising probabilistic processes logically

Yuxin Deng^*
, Rob Van Glabbeek

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

14 Scopus citations

Abstract

In this paper we work on (bi)simulation semantics of processes that exhibit both nondeterministic and probabilistic behaviour. We propose a probabilistic extension of the modal mu-calculus and show how to derive characteristic formulae for various simulation-like preorders over finite-state processes without divergence. In addition, we show that even without the fixpoint operators this probabilistic mu-calculus can be used to characterise these behavioural relations in the sense that two states are equivalent if and only if they satisfy the same set of formulae.

Original language	English
Title of host publication	Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings
Editors	Christian G. Fermuller
Pages	278-293
Number of pages	16
DOIs	https://doi.org/10.1007/978-3-642-16242-8-20
State	Published - 2010
Externally published	Yes
Event	17th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR-17 - Yogyakarta, Indonesia Duration: 10 Oct 2010 → 15 Oct 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6397 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR-17
Country/Territory	Indonesia
City	Yogyakarta
Period	10/10/10 → 15/10/10

Access to Document

10.1007/978-3-642-16242-8-20

Cite this

Deng, Y., & Van Glabbeek, R. (2010). Characterising probabilistic processes logically. In C. G. Fermuller (Ed.), Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings (pp. 278-293). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6397 LNCS). https://doi.org/10.1007/978-3-642-16242-8-20

Deng, Yuxin ; Van Glabbeek, Rob. / Characterising probabilistic processes logically. Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings. editor / Christian G. Fermuller. 2010. pp. 278-293 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "In this paper we work on (bi)simulation semantics of processes that exhibit both nondeterministic and probabilistic behaviour. We propose a probabilistic extension of the modal mu-calculus and show how to derive characteristic formulae for various simulation-like preorders over finite-state processes without divergence. In addition, we show that even without the fixpoint operators this probabilistic mu-calculus can be used to characterise these behavioural relations in the sense that two states are equivalent if and only if they satisfy the same set of formulae.",

author = "Yuxin Deng and \{Van Glabbeek\}, Rob",

year = "2010",

doi = "10.1007/978-3-642-16242-8-20",

language = "英语",

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booktitle = "Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings",

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Deng, Y & Van Glabbeek, R 2010, Characterising probabilistic processes logically. in CG Fermuller (ed.), Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6397 LNCS, pp. 278-293, 17th International Conference on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR-17, Yogyakarta, Indonesia, 10/10/10. https://doi.org/10.1007/978-3-642-16242-8-20

Characterising probabilistic processes logically. / Deng, Yuxin; Van Glabbeek, Rob.
Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings. ed. / Christian G. Fermuller. 2010. p. 278-293 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6397 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this paper we work on (bi)simulation semantics of processes that exhibit both nondeterministic and probabilistic behaviour. We propose a probabilistic extension of the modal mu-calculus and show how to derive characteristic formulae for various simulation-like preorders over finite-state processes without divergence. In addition, we show that even without the fixpoint operators this probabilistic mu-calculus can be used to characterise these behavioural relations in the sense that two states are equivalent if and only if they satisfy the same set of formulae.

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Deng Y, Van Glabbeek R. Characterising probabilistic processes logically. In Fermuller CG, editor, Logic for Programming, Artificial Intelligence, and Reasoning - 17th International Conference, LPAR-17, Proceedings. 2010. p. 278-293. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-16242-8-20

Characterising probabilistic processes logically

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