Bayes networks for estimating the number of solutions to a CSP

Research output: Contribution to conferencePaperpeer-review

10 Scopus citations

Abstract

The problem of counting the number of solutions to a constraint satisfaction problem (CSP) is rephrased in terms of probability updating in Bayes networks. Approximating the probabilities in Bayes networks is a problem which has been studied for a while, and may well provide a good approximation to counting the number of solutions. We use a simple approximation based on independence, and show that it is correct for tree-structured CSPs. For other CSPs, it is a less optimistic approximation than those suggested in prior work, and experiments show that it is more accurate on the average. We present empirical evidence that our approximation is a useful search heuristic for finding a single solution to a CSP.

Original languageEnglish
Pages179-184
Number of pages6
StatePublished - 1 Dec 1997
EventProceedings of the 1997 14th National Conference on Artificial Intelligence, AAAI 97 - Providence, RI, USA
Duration: 27 Jul 199731 Jul 1997

Conference

ConferenceProceedings of the 1997 14th National Conference on Artificial Intelligence, AAAI 97
CityProvidence, RI, USA
Period27/07/9731/07/97

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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