The Inductive Constraint Programming Loop
Résumé
Constraint programming is used for a variety of real-world optimiza- tion problems, such as planning, scheduling and resource allocation prob- lems. 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, that we call the Inductive Constraint Programming (ICON) loop. In this approach data is gathered and analyzed systemati- cally in order to dynamically revise and adapt constraints and optimiza- tion 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 hand.
Domaines
Intelligence artificielle [cs.AI]Origine | Fichiers produits par l'(les) auteur(s) |
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