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The next best solution

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

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

    2 Scopus citations

    Abstract

    We study the computational complexity of finding the next most preferred solution in some common formalisms for representing constraints and preferences. The problem is computationally intractable for CSPs, but is polynomial for tree-shaped CSPs and tree-shaped fuzzy CSPs. On the other hand, it is intractable for weighted CSPs, even under restrictions on the constraint graph. For CP-nets, the problem is polynomial when the CP-net is acyclic. This remains so if we add (soft) constraints that are tree-shaped and topologically compatible with the CP-net.

    Original languageEnglish
    Title of host publicationAAAI-11 / IAAI-11 - Proceedings of the 25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference
    Pages1537-1540
    Number of pages4
    StatePublished - 2 Nov 2011
    Event25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11 - San Francisco, CA, United States
    Duration: 7 Aug 201111 Aug 2011

    Publication series

    NameProceedings of the National Conference on Artificial Intelligence
    Volume2

    Conference

    Conference25th AAAI Conference on Artificial Intelligence and the 23rd Innovative Applications of Artificial Intelligence Conference, AAAI-11 / IAAI-11
    Country/TerritoryUnited States
    CitySan Francisco, CA
    Period7/08/1111/08/11

    ASJC Scopus subject areas

    • Software
    • Artificial Intelligence

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