01359nas a2200205   4500008004100000245004600041210004200087520074100129100002400870700001800894700001500912700001900927700001700946700002300963700002200986700002601008700002001034700002001054856007901074       2017                        eng d00aThe Inductive Constraint Programming Loop0 aInductive Constraint Programming Loop3 aConstraint programming is used for a variety of real-world optimization problems, such as planning, scheduling and resource allocation problems. At the same time, one continuously gathers vast amounts of data about these problems. Current constraint programming software does not exploit such data to update schedules, resources and plans. We propose a new framework, which we call the inductive constraint programming loop. In this approach data is gathered and analyzed systematically in order to dynamically revise and adapt constraints and optimization criteria. Inductive Constraint Programming aims at bridging the gap between the areas of data mining and machine learning on the one hand, and constraint programming on the other.1 aBessiere, Christian1 aDe Raedt, Luc1 aGuns, Tias1 aKotthoff, Lars1 aNanni, Mirco1 aNijssen, Siegfried1 aO'Sullivan, Barry1 aPaparrizou, Anastasia1 aPedreschi, Dino1 aSimonis, Helmut  uhttps://kdd.isti.cnr.it/publications/inductive-constraint-programming-loop