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Raphaël Chenouard

dblp:31/2539 · DBLP profile ↗
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5ranked-venue papers
4as first author
0since 2021 · last 2013
0000-0002-9761-6703ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-authorSoftware engineering, systems software and programming languages · 3 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorTheory of computation · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 100%
Theoretical computer science
1 paper
Algorithms and data structures · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithms and data structures
anytime algorithms		 0.112009
Search Strategies for an Anytime Usage of the Branch and Prune Algorithm · IJCAI 2009

Methods — techniques the papers use, named apart from their topics

branch-and-prune · 0.2search strategy · 0.1search strategies · 0.1
YearPublicationVenuePosition
2013 Constraint based approach for the steady-state simulation of complex systems: Application to ship control
Vincent Larroudé, Raphaël Chenouard, Pierre-Alain Yvars, Dominique Millet
 Eng. Appl. Artif. Intell.2
2009 Search Strategies for an Anytime Usage of the Branch and Prune Algorithm
Raphaël Chenouard, Alexandre Goldsztejn, Christophe Jermann
 IJCAI1
2009 Automatically Discovering Hidden Transformation Chaining Constraints
Raphaël Chenouard, Frédéric Jouault
 MoDELS1
2008 Model-driven constraint programming
abstract
Constraint programming can definitely be seen as a model-driven paradigm. The users write programs for modeling problems. These programs are mapped to executable models to calculate the solutions. This paper focuses on efficient model management (definition and transformation). From this point of view, we propose to revisit the design of constraint-programming systems. A model-driven architecture is introduced to map solving-independent constraint models to solving-dependent decision models. Several important questions are examined, such as the need for a visual highlevel modeling language, and the quality of metamodeling techniques to implement the transformations. A main result is the s-COMMA platform that efficiently implements the chain from modeling to solving constraint problems
Raphaël Chenouard, Laurent Granvilliers, Ricardo Soto 0001
 PPDP1
2007 Solving an Air Conditioning System Problem in an Embodiment Design Context Using Constraint Satisfaction Techniques
Raphaël Chenouard, Patrick Sébastian, Laurent Granvilliers
 CP1