Learning How to Propagate Using Random Probing

Abstract. In constraint programming there are often many choices regarding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usually only apply a standard method, typically (generalized) arc consistency, on all constraints throughout search. Advanced solvers additionally allow for the modeler to choose among an array of propagators for certain (global) constraints. Since complex interactions exist among constraints, deciding in the modelling phase which propagation method to use on given constraints can be a hard task that ideally we would like to free the user from. In this paper we propose a simple technique towards the automation of this task. Our approach exploits information gathered from a random probing preprocessing phase to automatically decide on the propagation method to be used on each constraint. As we demonstrate, data gathered though probing allows for the solver to accurately differentiate between constraints that oï¬...

• Type: Conference
• Year: 2009
• Where: CPAIOR
• Authors: Efstathios Stamatatos, Kostas Stergiou
• Keywords: Constraint Programming, CPAIOR 2009, Discrete Geometry, Propagation Methods, Simple Constraint Solvers