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» Statistical Modelling of CSP Solving Algorithms Performance
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AAAI
1994
13 years 9 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex
SAT
2005
Springer
133views Hardware» more  SAT 2005»
14 years 1 months ago
Solving Over-Constrained Problems with SAT Technology
Abstract. We present a new generic problem solving approach for overconstrained problems based on Max-SAT. We first define a clausal form formalism that deals with blocks of clau...
Josep Argelich, Felip Manyà
AI
2005
Springer
13 years 7 months ago
The distributed breakout algorithms
We present a new series of distributed constraint satisfaction algorithms, the distributed breakout algorithms, which is inspired by local search algorithms for solving the constr...
Katsutoshi Hirayama, Makoto Yokoo
CVPR
2011
IEEE
13 years 4 months ago
High-Frequency Shape and Albedo from Shading using Natural Image Statistics
We relax the long-held and problematic assumption in shape-from-shading (SFS) that albedo must be uniform or known, and address the problem of “shape and albedo from shading” ...
Jonathan Barron, Jitendra Malik
ECAI
1992
Springer
13 years 11 months ago
Arc-Consistency for Non-Binary Dynamic CSPs
Constraint satisfaction problems (CSPs) provide a model often used in Artificial Intelligence. Since the problem of the existence of a solution in a CSP is an NP-complete task, man...
Christian Bessière