Verifying Preferential Equivalence and Subsumption via Model Checking

Ganesh Ram Santhanam, Samik Basu, Vasant Honavar

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

1 Scopus citations

Abstract

We present a practical, model checking based, approach to verifying whether a set of ceteris paribus preference statements is equivalent to or is subsumed by another. We translate a given pair of sets of preference statements into a labeled transition system (LTS) and reduce the problem of determining whether one set of preference statements is equivalent to or is subsumed by the other to verifying the appropriate computation-tree temporal logic (CTL) formulas in the resulting LTS. Whenever the two sets of preference statements are not equivalent, our method outputs a dominance relationship that is induced by one and not by the other. Our approach is applicable to all preference languages based on ceteris paribus semantics including CP-nets, TCP-nets, CI-nets and CP-Theories.

Original languageEnglish (US)
Title of host publicationAlgorithmic Decision Theory - Third International Conference, ADT 2013, Proceedings
Pages324-335
Number of pages12
DOIs
StatePublished - Dec 16 2013
Event3rd International Conference on Algorithmic Decision Theory, ADT 2013 - Bruxelles, Belgium
Duration: Nov 13 2013Nov 15 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8176 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Algorithmic Decision Theory, ADT 2013
CountryBelgium
CityBruxelles
Period11/13/1311/15/13

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Santhanam, G. R., Basu, S., & Honavar, V. (2013). Verifying Preferential Equivalence and Subsumption via Model Checking. In Algorithmic Decision Theory - Third International Conference, ADT 2013, Proceedings (pp. 324-335). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8176 LNAI). https://doi.org/10.1007/978-3-642-41575-3-25