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Constraint problems learning
Constraint programming allows to model many kind of problems with efficient solving methods. However, its complexity has increased these last years and its use,... -
Learning Characteristic Rules Relying on Quantified Paths
In this paper, we address the characterization task and we present a general framework for the characterization of a target set of objects by means of their own... -
Logical settings for concept learning from incomplete examples in First Order...
We investigate here concept learning from incomplete examples. Our first purpose is to discuss to what extent logical learning settings have to be modified in order to... -
Supervised Relational Machine Learning using Evolutionary Algorithms
U.F.R. Scientifique d'Orsay N° d'ordre: 6420 -
Completing causal networks by meta-level abduction
International audience
