Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
An introduction to variational methods for graphical models
Learning in graphical models
Survey propagation: An algorithm for satisfiability
Random Structures & Algorithms
A new look at survey propagation and its generalizations
Journal of the ACM (JACM)
Probabilistically Estimating Backbones and Variable Bias: Experimental Overview
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
Complete local search for propositional satisfiability
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Using expectation maximization to find likely assignments for solving CSP's
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
SATzilla: portfolio-based algorithm selection for SAT
Journal of Artificial Intelligence Research
Backdoors to typical case complexity
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Random Formulas Have Frozen Variables
SIAM Journal on Computing
Solution counting algorithms for constraint-centered search heuristics
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Iterative join-graph propagation
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Implementing survey propagation on graphics processing units
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
Characterizing propagation methods for boolean satisfiability
SAT'06 Proceedings of the 9th international conference on Theory and Applications of Satisfiability Testing
CSCLP'04 Proceedings of the 2004 joint ERCIM/CoLOGNET international conference on Recent Advances in Constraints
Factor graphs and the sum-product algorithm
IEEE Transactions on Information Theory
Automated testing and debugging of SAT and QBF solvers
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
On the interpolation between product-based message passing heuristics for SAT
SAT'13 Proceedings of the 16th international conference on Theory and Applications of Satisfiability Testing
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Probabilistic inference techniques can be used to estimate variable bias , or the proportion of solutions to a given SAT problem that fix a variable positively or negatively. Methods like Belief Propagation (BP), Survey Propagation (SP), and Expectation Maximization BP (EMBP) have been used to guess solutions directly, but intuitively they should also prove useful as variable- and value- ordering heuristics within full backtracking (DPLL) search. Here we report on practical design issues for realizing this intuition in the VARSAT system, which is built upon the full-featured MiniSat solver. A second, algorithmic, contribution is to present four novel inference techniques that combine BP/SP models with local/global consistency constraints via the EMBP framework. Empirically, we can also report exponential speed-up over existing complete methods, for random problems at the critically-constrained phase transition region in problem hardness. For industrial problems, VARSAT is slower that MiniSat, but comparable in the number and types problems it is able to solve.