Back to Search
Start Over
The inductive constraint programming loop
- Source :
- IEEE Intelligent Systems, IEEE Intelligent Systems, Institute of Electrical and Electronics Engineers, 2017, 32 (5), pp.44-52. ⟨10.1109/MIS.2017.3711637⟩, Vrije Universiteit Brussel, Data Mining and Constraint Programming-Foundations of a Cross-Disciplinary Approach, 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⟩, Data Mining and Constraint Programming ISBN: 9783319501369, Data Mining and Constraint Programming
- Publication Year :
- 2016
- Publisher :
- Springer, 2016.
-
Abstract
- Constraint programming is used for a variety of real-world optimisation 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, that 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 hand.<br />17 pages, 9 figures
- Subjects :
- FOS: Computer and information sciences
Concurrent constraint logic programming
Mathematical optimization
constraint programming
Optimization problem
Theoretical computer science
Exploit
Computer science
Computer Science - Artificial Intelligence
Computer Networks and Communications
0211 other engineering and technologies
Scheduling (production processes)
02 engineering and technology
Theoretical Computer Science
Computer Science (all)
artificial intelligence
data mining
intelligent systems
machine learning
Artificial Intelligence
Machine Learning (cs.LG)
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Software
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
Constraint programming
Reactive programming
021103 operations research
LOOP (programming language)
business.industry
Constraint satisfaction
Inductive programming
Variety (cybernetics)
Computer Science - Learning
Artificial Intelligence (cs.AI)
Procedural programming
Programming paradigm
Resource allocation
020201 artificial intelligence & image processing
business
Functional reactive programming
Subjects
Details
- Language :
- English
- ISBN :
- 978-3-319-50136-9
- ISSN :
- 15411672
- ISBNs :
- 9783319501369
- Database :
- OpenAIRE
- Journal :
- IEEE Intelligent Systems, IEEE Intelligent Systems, Institute of Electrical and Electronics Engineers, 2017, 32 (5), pp.44-52. ⟨10.1109/MIS.2017.3711637⟩, Vrije Universiteit Brussel, Data Mining and Constraint Programming-Foundations of a Cross-Disciplinary Approach, 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⟩, Data Mining and Constraint Programming ISBN: 9783319501369, Data Mining and Constraint Programming
- Accession number :
- edsair.doi.dedup.....ff258191398078b6c1184cd5273df3f9