An adaptive noise mechanism for walkSAT
Eighteenth 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
Diversification and determinism in local search for satisfiability
SAT'05 Proceedings of the 8th international conference on Theory and Applications of Satisfiability Testing
Improving stochastic local search for SAT with a new probability distribution
SAT'10 Proceedings of the 13th international conference on Theory and Applications of Satisfiability Testing
Exploiting historical relationships of clauses and variables in local search for satisfiability
SAT'12 Proceedings of the 15th international conference on Theory and Applications of Satisfiability Testing
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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During local search, clauses may frequently be satisfied or falsified. Modern SLS algorithms often exploit the falsifying history of clauses to select a variable to flip, together with variable properties such as score and age. The score of a variable x refers to the decrease in the number of unsatisfied clauses if x is flipped. The age of x refers to the number of steps done since the last time when x was flipped.