The Inductive Constraint Programming Loop

Constraint 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...

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Bibliographic Details
Published in:IEEE intelligent systems p. 1
Main Authors: BESSIERE, Christian, de Raedt, Luc, Guns, Tias, Kotthoff, Lars, Nanni, Mirco, Nijssen, Siegfried, O'Sullivan, Barry, Paparrizou, Anastasia, Pedreschi, Dino, Simonis, Helmut
Format: Journal Article
Language:English
Published: IEEE 01.09.2017
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ISSN:1541-1672
Online Access:Get full text
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Summary:Constraint 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.
ISSN:1541-1672
DOI:10.1109/MIS.2017.265115706