Strong completeness for Markovian logics

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper we present Hilbert-style axiomatizations for three logics for reasoning about continuous-space Markov processes (MPs): (i) a logic for MPs defined for probability distributions on measurable state spaces, (ii) a logic for MPs defined for sub-probability distributions and (iii) a logic defined for arbitrary distributions. These logics are not compact so one needs infinitary rules in order to obtain strong completeness results. We propose a new infinitary rule that replaces the so-called Countable Additivity Rule (CAR) currently used in the literature to address the problem of proving strong completeness for these and similar logics. Unlike the CAR, our rule has a countable set of instances; consequently it allows us to apply the Rasiowa-Sikorski lemma for establishing strong completeness. Our proof method is novel and it can be used for other logics as well.
Original languageEnglish
Title of host publicationMathematical Foundations of Computer Science 2013
Subtitle of host publication38th International Symposium, MFCS 2013, Klosterneuburg, Austria, August 26-30, 2013, Proceedings
EditorsKrishnendu Chatterjee, Jirí Sgall
Place of PublicationBerlin
PublisherSpringer
Pages655-666
Number of pages12
Volume8087
ISBN (Electronic)978-3-642-40313-2
ISBN (Print)978-3-642-40312-5
DOIs
Publication statusPublished - Aug 2013

Publication series

NameLecture Notes in Computer Science
Volume8087
ISSN (Print)0302-9743

Keywords

  • markov process
  • logics
  • probability distributions
  • sub-probability distributions
  • arbitrary distributions

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