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Refined Bounds for Instance-Based Search Complexity of Counting and Other #P Problems

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Principles and Practice of Constraint Programming (CP 2008)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 5202))

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Abstract

We present measures for bounding the instance-based complexity of AND/OR search algorithms for solution counting and related #P problems. To this end we estimate the size of the search space, with special consideration given to the impact of determinism in a problem. The resulting schemes are evaluated empirically on a variety of problem instances and shown to be quite powerful.

This work is supported in part by NSF grant IIS-0713118 and NIH grant R01-HG004175-02.

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References

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Authors and Affiliations

  1. Bren School of Information and Computer Sciences, University of California, Irvine, CA 92697-3425, U.S.A.

    Lars Otten & Rina Dechter

Authors
  1. Lars Otten
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  2. Rina Dechter
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Peter J. Stuckey

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© 2008 Springer-Verlag Berlin Heidelberg

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Otten, L., Dechter, R. (2008). Refined Bounds for Instance-Based Search Complexity of Counting and Other #P Problems. In: Stuckey, P.J. (eds) Principles and Practice of Constraint Programming. CP 2008. Lecture Notes in Computer Science, vol 5202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85958-1_45

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  • DOI: https://doi.org/10.1007/978-3-540-85958-1_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85957-4

  • Online ISBN: 978-3-540-85958-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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