QG/GA: A Stochastic Search for Progol

摘要

A search approach is presented, based on a novel algorithm called QG (Quick Generalisation). QG carries out a random-restart stochastic bottom-up search which efficiently generates a consistent clause on the fringe of the refinement graph search without needing to explore the graph in detail. We use a Genetic Algorithm (GA) to evolve and re-combine clauses generated by QG. Initial experiments with QG/GA indicate that this approach can be more efficient than standard refinement-graph searches, while generating similar or better solutions.