Unsatis ed Variables in Local Search

Several local search algorithms for propositional satis ability have been pro posed which can solve hard random problems beyond the range of conventional backtracking procedures In this paper we explore the impact of focusing search in these procedures on the unsatis ed variables that is those variables which appear in clauses which are not yet satis ed For random problems we show that such a focus reduces the sensitivity to input parameters We also observe a simple scaling law in performance For non random problems we show that whilst this focus can improve performance many problems remain di cult We speculate that such problems will remain hard for local search unless constraint propagation techniques can be combined with hill climbing