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Upper and Lower Bounds on the Time Complexity of Infinite-Domain CSPs

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Book cover Principles and Practice of Constraint Programming (CP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9255))

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Abstract

The constraint satisfaction problem (CSP) is a widely studied problem with numerous applications in computer science. For infinite-domain CSPs, there are many results separating tractable and NP-hard cases while upper bounds on the time complexity of hard cases are virtually unexplored. Hence, we initiate a study of the worst-case time cmplexity of such CSPs. We analyse backtracking algorithms and show that they can be improved by exploiting sparsification. We present even faster algorithms based on enumerating finite structures. Last, we prove non-trivial lower bounds applicable to many interesting CSPs, under the assumption that the strong exponential-time hypothesis is true.

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Authors and Affiliations

  1. Department of Computer and Information Science, Linköping University, Linköping, Sweden

    Peter Jonsson & Victor Lagerkvist

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  1. Peter Jonsson
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  2. Victor Lagerkvist
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Correspondence to Victor Lagerkvist .

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Editors and Affiliations

  1. École Polytechnique de Montréal, Montréal, Québec, Canada

    Gilles Pesant

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Jonsson, P., Lagerkvist, V. (2015). Upper and Lower Bounds on the Time Complexity of Infinite-Domain CSPs. In: Pesant, G. (eds) Principles and Practice of Constraint Programming. CP 2015. Lecture Notes in Computer Science(), vol 9255. Springer, Cham. https://doi.org/10.1007/978-3-319-23219-5_14

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  • DOI: https://doi.org/10.1007/978-3-319-23219-5_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23218-8

  • Online ISBN: 978-3-319-23219-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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