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Unbiased Statistics of a Constraint Satisfaction Problem – a Controlled-Bias Generator

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Innovations in Computing Sciences and Software Engineering
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Abstract

We show that estimating the complexity (mean and distribution) of the instances of a fixed size Constraint Satisfaction Problem (CSP) can be very hard. We deal with the main two aspects of the problem: defining a measure of complexity and generating random unbiased instances. For the first problem, we rely on a general framework and a measure of complexity we presented at CISSE08. For the generation problem, we restrict our analysis to the Sudoku example and we provide a solution that also explains why it is so difficult.

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References

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Berthier, D. (2010). Unbiased Statistics of a Constraint Satisfaction Problem – a Controlled-Bias Generator. In: Sobh, T., Elleithy, K. (eds) Innovations in Computing Sciences and Software Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9112-3_16

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  • DOI: https://doi.org/10.1007/978-90-481-9112-3_16

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-9111-6

  • Online ISBN: 978-90-481-9112-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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