The Inductive Constraint Programming Loop - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2016

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.
Fichier principal
Vignette du fichier
icon-loop16.pdf (576.39 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02310649 , version 1 (10-10-2019)

Identifiants

Citer

Christian Bessiere, Luc de Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, et al.. The Inductive Constraint Programming Loop. Christian Bessiere; Luc De Raedt; Lars Kotthoff; Siegfried Nijssen; Barry O'Sullivan; Dino Pedreschi. Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach, LNCS (10101), Springer, pp.303-309, 2016, 978-3-319-50136-9. ⟨10.1007/978-3-319-50137-6_12⟩. ⟨hal-02310649⟩
53 Consultations
50 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More