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CP
2008
Springer

Probabilistically Estimating Backbones and Variable Bias: Experimental Overview

14 years 1 months ago
Probabilistically Estimating Backbones and Variable Bias: Experimental Overview
Backbone variables have the same assignment in all solutions to a given constraint satisfaction problem; more generally, bias represents the proportion of solutions that assign a variable a particular value. Intuitively such constructs would seem important to efficient search, but their study to date has been from a mostly conceptual perspective, in terms of indicating problem hardness or motivating and interpreting heuristics. Here we summarize a two-phase project where we first measure the ability of both existing and novel probabilistic message-passing techniques to directly estimate bias and identify backbones for the Boolean Satisfiability (SAT) Problem. We confirm that methods like Belief Propagation and Survey Propagation
Eric I. Hsu, Christian J. Muise, J. Christopher Be
Added 18 Oct 2010
Updated 18 Oct 2010
Type Conference
Year 2008
Where CP
Authors Eric I. Hsu, Christian J. Muise, J. Christopher Beck, Sheila A. McIlraith
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