Quantified Linear Temporal Logic over Probabilistic Systems with an Application to Vacuity Checking

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributedpeer-review

Contributors

Abstract

Quantified linear temporal logic (QLTL) is an ω-regular extension of LTL allowing quantification over propositional variables. We study the model checking problem of QLTL-formulas over Markov chains and Markov decision processes (MDPs) with respect to the number of quantifier alternations of formulas in prenex normal form. For formulas with k{-}1 quantifier alternations, we prove that all qualitative and quantitative model checking problems are k-EXPSPACE-complete over Markov chains and k{+}1-EXPTIME-complete over MDPs.
As an application of these results, we generalize vacuity checking for LTL specifications from the non-probabilistic to the probabilistic setting. We show how to check whether an LTL-formula is affected by a subformula, and also study inherent vacuity for probabilistic systems.

Details

Original languageEnglish
Title of host publication32nd International Conference on Concurrency Theory, CONCUR 2021
EditorsSerge Haddad, Daniele Varacca
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Pages7:1–7:18
ISBN (print)978-3-95977-203-7
Publication statusPublished - 1 Aug 2021
Peer-reviewedYes

Publication series

Series32nd International Conference on Concurrency Theory (CONCUR 2021) ; Vol. 203
Volume203
ISSN1868-8969

Conference

Title32nd International Conference on Concurrency Theory
Abbreviated titleCONCUR 2021
Duration23 - 27 August 2021
Website
Degree of recognitionInternational event
Locationonline
CityParis
CountryFrance

External IDs

ORCID /0000-0002-5321-9343/work/142236688
Scopus 85115305824
ORCID /0000-0003-4829-0476/work/165453929

Keywords

ASJC Scopus subject areas

Keywords

  • Markov chain, Markov decision process, Quantified linear temporal logic, vacuity, Vacuity