Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Stochastic Local Search: Foundations & Applications
Stochastic Local Search: Foundations & Applications
Boosting Verification by Automatic Tuning of Decision Procedures
FMCAD '07 Proceedings of the Formal Methods in Computer Aided Design
Automated discovery of local search heuristics for satisfiability testing
Evolutionary Computation
Calysto: scalable and precise extended static checking
Proceedings of the 30th international conference on Software engineering
SATenstein: automatically building local search SAT solvers from components
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
ParamILS: an automatic algorithm configuration framework
Journal of Artificial Intelligence Research
On the structure of industrial SAT instances
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
A new method for solving hard satisfiability problems
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Towards an understanding of hill-climbing procedures for SAT
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Evidence for invariants in local search
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
UBCSAT: an implementation and experimentation environment for SLS algorithms for SAT and MAX-SAT
SAT'04 Proceedings of the 7th international conference on Theory and Applications of Satisfiability Testing
Effective preprocessing in SAT through variable and clause elimination
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Diversification and determinism in local search for satisfiability
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Random walk with continuously smoothed variable weights
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Captain Jack: new variable selection heuristics in local search for SAT
SAT'11 Proceedings of the 14th international conference on Theory and application of satisfiability testing
Automatically configuring algorithms for scaling performance
LION'12 Proceedings of the 6th international conference on Learning and Intelligent Optimization
Ordered racing protocols for automatically configuring algorithms for scaling performance
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Local search for Boolean Satisfiability with configuration checking and subscore
Artificial Intelligence
Comprehensive score: towards efficient local search for SAT with long clauses
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Weight-enhanced diversification in stochastic local search for satisfiability
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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We introduce a new conceptual model for representing and designing Stochastic Local Search (SLS) algorithms for the propositional satisfiability problem (SAT). Our model can be seen as a generalization of existing variable weighting, scoring and selection schemes; it is based upon the concept of Variable Expressions (VEs), which use properties of variables in dynamic scoring functions. Algorithms in our model are constructed from conceptually separated components: variable filters, scoring functions (VEs), variable selection mechanisms and algorithm controllers. To explore the potential of our model we introduce the Design Architecture for Variable Expressions (DAVE), a software framework that allows users to specify arbitrarily complex algorithms at run-time. Using DAVE, we can easily specify rich design spaces of SLS algorithms and subsequently explore these using an automated algorithm configuration tool. We demonstrate that by following this approach, we can achieve significant improvements over previous state-of-the-art SLS-based SAT solvers on software verification benchmark instances from the literature.