Finding the next solution in constraint-and preference-based knowledge representation formalisms

R. Brafman, F. Rossi, D. Salvagnin, K. B. Venable, T. Walsh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

In constraint or preference reasoning, a typical task is to compute a solution, or an optimal solution. However, when one has already a solution, it may be important to produce the next solution following the given one in a linearization of the solution ordering where more preferred solutions are ordered first. In this paper, we study the computational complexity of finding the next solution in some common preference-based representation formalisms. We show that this problem is hard in general CSPs, but it can be easy in tree-shaped CSPs and tree-shaped fuzzy CSPs. However, it is difficult in weighted CSPs, even if we restrict the shape of the constraint graph. We also consider CP-nets, showing that the problem is easy in acyclic CP-nets, as well as in constrained acyclic CP-nets where the (soft) constraints are tree-shaped and topologically compatible with the CP-net.

Original languageEnglish
Title of host publicationPrinciples of Knowledge Representation and Reasoning
Subtitle of host publicationProceedings of the 12th International Conference, KR 2010
PublisherInstitute of Electrical and Electronics Engineers
Pages425-433
Number of pages9
ISBN (Print)9781577354512
StatePublished - 1 Jan 2010
Event12th International Conference on Principles of Knowledge Representation and Reasoning, KR 2010 - Toronto, ON, Canada
Duration: 9 May 201013 May 2010

Publication series

NameProceedings of the International Conference on Knowledge Representation and Reasoning
ISSN (Print)2334-1025
ISSN (Electronic)2334-1033

Conference

Conference12th International Conference on Principles of Knowledge Representation and Reasoning, KR 2010
Country/TerritoryCanada
CityToronto, ON
Period9/05/1013/05/10

ASJC Scopus subject areas

  • Logic

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