Constraint Programming is an attractive approach for solving AI planning problems by modelling them as Constraint Satisfaction Problems (CSPs). However, formulating effective cons...
Andrea Rendl, Ian Miguel, Ian P. Gent, Peter Grego...
Abstract. Neuroimaging at the group level requires spatial normalization of individual structural data. We propose a geometric approach that consists in matching a series of cortic...
Guillaume Auzias, Joan Glaunes, Olivier Colliot, M...
Temporal logics and model-checking have proved successful to respectively express biological properties of complex biochemical systems, and automatically verify their satisfaction...
Finding a constraint network that will be efficiently solved by a constraint solver requires a strong expertise in Constraint Programming. Hence, there is an increasing interest i...
We present a simple generic framework to solve constraints on any domain (finite or infinite) which has a lattice structure. The approach is based on the use of a single constrai...