From Support Propagation to Belief Propagation in Constraint Programming

On the Power of Belief Propagation: A Constraint Propagation Perspective

In his seminal paper, Pearl [1986] introduced the notion of Bayesian networks and the first processing algorithm, Belief Propagation (BP), that computes posterior marginals, called beliefs, for each variable when the network is singly connected. The paper provided the foundation for the whole area of Bayesian networks. It was the first in a series of influential papers by Pearl, his students an...

Belief propagation algorithms for constraint satisfaction problems

Belief propagation algorithms for constraint satisfaction problems by Elitza Nikolaeva Maneva Doctor of Philosophy in Computer Science and the Designated Emphasis in Communication, Computation, and Statistics University of California, Berkeley Professor Alistair Sinclair, Chair We consider applications of belief propagation algorithms to Boolean constraint satisfaction problems (CSPs), such as ...

Multi-Objective Propagation in Constraint Programming

Bounding constraints are used to bound the tolerance of solutions under certain undesirable features. Standard solvers propagate them one by one. Often times, it is easy to satisfy them independently, but difficult to satisfy them simultaneously. Therefore, the standard propagation methods fail. In this paper we propose a novel approach inspired in multi-objective optimization. We compute a mul...

Programming Constraint Propagation in Rea tive Rules

Linear programming and variants of Belief Propagation

1 Linear programming and variants of Belief Propagation 2 1.