A General Framework for Probabilistic Characterizing Formulae

Publication: Research - peer-reviewConference article – Annual report year: 2012

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Recently, a general framework on characteristic formulae was proposed by Aceto et al. It offers a simple theory that allows one to easily obtain characteristic formulae of many non-probabilistic behavioral relations. Our paper studies their techniques in a probabilistic setting. We provide a general method for determining characteristic formulae of behavioral relations for probabilistic automata using fixed-point probability logics. We consider such behavioral relations as simulations and bisimulations, probabilistic bisimulations, probabilistic weak simulations, and probabilistic forward simulations. This paper shows how their constructions and proofs can follow from a single common technique.
Original languageEnglish
Book seriesLecture Notes in Computer Science
Publication date2012
Volume7148
Pages396-411
ISSN0302-9743
DOIs
StatePublished

Conference

Conference13th International Conference on Verification, Model Checking, and Abstract Interpretation
CityPhiladelphia, Pennsylvania, USA
Period01/01/12 → …
CitationsWeb of Science® Times Cited: No match on DOI
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