A Spectrum of Approximate Probabilistic Bisimulations

Research output: Contribution to book/Conference proceedings/Anthology/ReportConference contributionContributedpeer-review

Contributors

Abstract

This paper studies various notions of approximate probabilistic bisimulation on labeled Markov chains (LMCs). We introduce approximate versions of weak and branching bisimulation, as well as a notion of ε-perturbed bisimulation that relates LMCs that can be made (exactly) probabilistically bisimilar by small perturbations of their transition probabilities. We explore how the notions interrelate and establish their connections to other well-known notions like ε-bisimulation.

Details

Original languageEnglish
Title of host publication35th International Conference on Concurrency Theory (CONCUR 2024)
EditorsRupak Majumdar, Alexandra Silva
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (electronic)978-3-95977-339-3
Publication statusPublished - 29 Aug 2024
Peer-reviewedYes

Publication series

SeriesLeibniz International Proceedings in Informatics, LIPIcs
Volume311
ISSN1868-8969

Conference

TitleInternational Conference on Concurrency Theory
Abbreviated titleCONCUR 2024
Conference number35
Duration9 - 13 September 2024
Website
Degree of recognitionInternational event
LocationBest Western Plus Village Park Inn
CityCalgary
CountryCanada

External IDs

Scopus 85203497328
ORCID /0000-0002-5321-9343/work/173985295
ORCID /0000-0003-4829-0476/work/173987796
ORCID /0009-0008-4461-0667/work/173989272

Keywords

ASJC Scopus subject areas

Keywords

  • Abstraction, Approximate bisimulation, Markov chains, Model checking