CPR for CSPs: A Probabilistic Relaxation of Constraint Propagation

Part of Advances in Neural Information Processing Systems 20 (NIPS 2007)

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Authors

Luis E. Ortiz

Abstract

This paper proposes constraint propagation relaxation (CPR), a probabilistic approach to classical constraint propagation that provides another view on the whole parametric family of survey propagation algorithms SP(ρ), ranging from belief propagation (ρ = 0) to (pure) survey propagation(ρ = 1). More importantly, the approach elucidates the implicit, but fundamental assumptions underlying SP(ρ), thus shedding some light on its effectiveness and leading to applications beyond k-SAT.