Abstract

The n-queens problem is a classical combinatorial problem in the artificial intelligence (AI) area. Since the problem has a simple and regular structure, it has been widely used as a testbed to develop and benchmark new AI search problem-solving strategies. Recently, this problem has found practical applications in VLSI testing and traffic control. Due to its inherent complexity, currently even very efficient AI search algorithms developed so far can only find a solution for the n-queens problem with n up to about 100. In this paper we present a new, probabilistic local search algorithm which is based on a gradient-based heuristic. This efficient algorithm is capable of finding a solution for extremely large size n-queens problems. We give the execution statistics for this algorithm with n up to 500,000.