Giorgio Bacci ; Giovanni Bacci ; Kim G. Larsen ; Radu Mardare - A Complete Quantitative Deduction System for the Bisimilarity Distance on Markov Chains

lmcs:3130 - Logical Methods in Computer Science, November 16, 2018, Volume 14, Issue 4 - https://doi.org/10.23638/LMCS-14(4:15)2018
A Complete Quantitative Deduction System for the Bisimilarity Distance on Markov ChainsArticle

Authors: Giorgio Bacci ORCID; Giovanni Bacci ORCID; Kim G. Larsen ; Radu Mardare

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 $t \equiv_\varepsilon s$ indexed by rationals, expressing that `$t$ is approximately equal to $s$ up to an error $\varepsilon$'. 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).

Comment: Logical Methods in Computer Science


Volume: Volume 14, Issue 4
Secondary volumes: Selected Papers of the 27th International Conference on Concurrency Theory (CONCUR 2016)
Published on: November 16, 2018
Accepted on: November 14, 2018
Submitted on: February 9, 2017
Keywords: Computer Science - Logic in Computer Science
Funding:
    Source : OpenAIRE Graph
  • Self Energy-Supporting Autonomous Computation; Funder: European Commission; Code: 318490
  • Learning, Analysis, SynthesiS and Optimization of Cyber-Physical Systems; Funder: European Commission; Code: 669844
  • Collective Adaptive System SynThesIs with Non-zero-sum Games; Funder: European Commission; Code: 601148

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