Unbiased Statistics of a CSP - A Controlled-Bias Generator

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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Contributor : Denis Berthier <>
Submitted on : Thursday, November 17, 2011 - 7:39:38 AM
Last modification on : Wednesday, September 12, 2018 - 3:40:03 PM
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  • HAL Id : hal-00641955, version 1
  • ARXIV : 1111.4083


Denis Berthier. Unbiased Statistics of a CSP - A Controlled-Bias Generator. Khaled Elleithy. Innovations in Computing Sciences and Software Engineering, Springer, pp.165-170, 2010. ⟨hal-00641955⟩



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