Local Search Strategies for Satis

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 f...

A New Method for Solving Hard Satis ability Problems

We introduce a greedy local search procedure called GSAT for solving propositional satis ability problems Our experiments show that this procedure can be used to solve hard randomly generated problems that are an order of magnitude larger than those that can be handled by more traditional approaches such as the Davis Putnam procedure or resolution We also show that GSAT can solve structured sat...

The Search for Satisfaction

In recent years, there has been an explosion of research in AI into propositional satis ability (or Sat). There are many factors behind the increased interest in this area. One factor is the improvement in search procedures for Sat. New local search procedures like Gsat are able to solve Sat problems with thousands of variables. At the same time, implementations of complete search algorithms li...

Solving Satis ability Problems Using a Combination of Systematic and Local Search

When Gravity Fails: Local Search Topology

Local search algorithms for combinatorial search problems frequently encounter a sequence of states in which it is impossible to improve the value of the objective function; moves through these regions, called plateau moves, dominate the time spent in local search. We analyze and characterize plateaus for three di erent classes of randomly generated Boolean Satis ability problems. We identify s...