Using stochastic methods to guide search in CLP: A preliminary report

Abstract

Recently Lee, Stuckey and Tam have shown the advantages of incorporating stochastic solvers into constraint logic programming (CLP) systems. Then-approaches, while efficient, both suffer from some form of incompleteness and complication in semantics. This paper proposes a generalization of these previous efforts by using stochastic methods to guide and speed up the search of derivation trees for successful branches. By spending computational effort to exercise the stochastic solver at various nodes in the derivation tree, additional information is obtained to suggest (a) delaying exploration of unpromising subtrees and (b) visiting promising children first. Using these simple guidelines we g..