A complete quantitative deduction system for the bisimilarity distance on Markov chains

Giorgio Bacci, Giovanni Bacci, Kim G. Larsen, Radu Mardare

Research output: Contribution to journalArticle

Abstract

In this paper we propose a complete axiomatization of the bisimilarity distance of Desharnais et al. for the class of finite labelled Markov chains. Our axiomatization is given in the style of a quantitative extension of equational logic recently proposed by Mardare, Panangaden, and Plotkin (LICS 2016) that uses equality relations t ≡ ε s indexed by rationals, expressing that “t is approximately equal to s up to an error ε”. Notably, our quantitative deduction system extends in a natural way the equational system for probabilistic bisimilarity given by Stark and Smolka by introducing an axiom for dealing with the Kantorovich distance between probability distributions. The axiomatization is then used to propose a metric extension of a Kleene’s style representation theorem for finite labelled Markov chains, that was proposed (in a more general coalgebraic fashion) by Silva et al. (Inf. Comput. 2011).

LanguageEnglish
Article number15
Number of pages29
JournalLogical Methods in Computer Science
Volume14
Issue number4
DOIs
Publication statusPublished - 16 Nov 2018

Fingerprint

Axiomatization
Deduction
Markov processes
Markov chain
Equational Logic
Probability distributions
Approximately equal
Representation Theorem
Axiom
Equality
Probability Distribution
Metric
Style

Keywords

  • axiomatization
  • behavioral distances
  • Markov chains

Cite this

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A complete quantitative deduction system for the bisimilarity distance on Markov chains. / Bacci, Giorgio; Bacci, Giovanni; Larsen, Kim G.; Mardare, Radu.

In: Logical Methods in Computer Science, Vol. 14, No. 4, 15, 16.11.2018.

Research output: Contribution to journalArticle

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