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Backtrack-Free and Backtrack-Bounded Search

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Search in Artificial Intelligence

Part of the book series: Symbolic Computation ((1064))

Abstract

Conditions are identified under which bounds can be placed on the amount of backtracking required to solve constraint satisfaction search problems. These relate the structure of the problem to the structure of the search sequence. Particular attention is paid to tree-structured constraint satisfaction problems. Problem complexity is shown to have a bound exponential in the size of the largest biconnected component of the problem’s constraint graph.

This material is based in part upon work supported by the National Science Foundation under Grants No. TICS 80-03307 and DCR. 8601209. The chapter is largely based on two papers [8, 9] which appeared in the Journal of the ACM.

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Author information

Authors and Affiliations

  1. Computer Science Department, University of New Hampshire, Durham, NH, 03824, USA

    Eugene C. Freuder

Authors
  1. Eugene C. Freuder
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Maryland, 20742, College Park, MD, USA

    Laveen Kanal

  2. Computer Science Department, University of Texas at Austin, 78712-1188, Austin, TX, USA

    Vipin Kumar

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© 1988 Springer-Verlag New York Inc.

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Freuder, E.C. (1988). Backtrack-Free and Backtrack-Bounded Search. In: Kanal, L., Kumar, V. (eds) Search in Artificial Intelligence. Symbolic Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-8788-6_10

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  • DOI: https://doi.org/10.1007/978-1-4613-8788-6_10

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4613-8790-9

  • Online ISBN: 978-1-4613-8788-6

  • eBook Packages: Springer Book Archive

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