Computing optimal subsets

Maxim Binshtok, Ronen I. Brafman, Solomon E. Shimony, Ajay Martin, Craig Boutilier

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

1 Scopus citations

Abstract

Various tasks in decision making and decision support require selecting a preferred subset of items from a given set of feasible items. Recent work in this area considered methods for specifying such preferences based on the attribute values of individual elements within the set. Of these, the approach of (Brafman et al. 2006) appears to be the most general. In this paper, we consider the problem of computing an optimal subset given such a specification. The problem is shown to be NP-hard in the general case, necessitating heuristic search methods. We consider two algorithm classes for this problem: direct set construction, and implicit enumeration as solutions to appropriate CSPs. New algorithms are presented in each class and compared empirically against previous results.

Original languageEnglish
Title of host publicationPreference Handling for Artificial Intelligence - Papers from the 2007 AAAI Workshop, Technical Report
Pages23-30
Number of pages8
StatePublished - 1 Dec 2007
Event2007 AAAI Workshop - Vancouver, BC, Canada
Duration: 22 Jul 200722 Jul 2007

Publication series

NameAAAI Workshop - Technical Report
VolumeWS-07-10

Conference

Conference2007 AAAI Workshop
Country/TerritoryCanada
CityVancouver, BC
Period22/07/0722/07/07

ASJC Scopus subject areas

  • Engineering (all)

Fingerprint

Dive into the research topics of 'Computing optimal subsets'. Together they form a unique fingerprint.

Cite this