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Christopher G. Reeson

dblp:97/6729 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 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
2 papers
Planning, search and constraint satisfaction · 100%
Databases, data mining, and information retrieval
1 paper
Database theory · 100%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
constraint propagation
0.112010
A First Practical Algorithm for High Levels of Relational Consistency · AAAI 2010
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › local consistency
relational consistency
0.112010
A First Practical Algorithm for High Levels of Relational Consistency · AAAI 2010
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
constraint programming
0.012007
An Interactive Constraint-Based Approach to Sudoku · AAAI 2007

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

wr(*,m)c · 0.2r(*,m)c · 0.2constraint propagation · 0.1
YearPublicationVenuePosition
2010 A First Practical Algorithm for High Levels of Relational Consistency
abstract
Consistency properties and algorithms for achieving them are at the heart of the success of Constraint Programming. In this paper, we study the relational consistency property R(*,m)C, which is equivalent to m-wise consistency proposed in relational databases. We also define wR(*,m)C, a weaker variant of this property. We propose an algorithm for enforcing these properties on a Constraint Satisfaction Problem by tightening the existing relations and without introducing new ones. We empirically show that wR(*,m)C solves in a backtrack-free manner all the instances of some CSP benchmark classes, thus hinting at the tractability of those classes.
Shant Kirakos Karakashian, Robert J. Woodward, Christopher G. Reeson, Berthe Y. Choueiry, Christian Bessiere
AAAI3
2007 An Interactive Constraint-Based Approach to Sudoku
Christopher G. Reeson, Kai-Chen Huang, Kenneth M. Bayer, Berthe Y. Choueiry
AAAI1