文献类型： 会议论文

第一作者： S. Augier

作者： S. Augier ¹ ; G. Venturini ² ; Y. Kodrato ¹ ;

作者机构： 1.Equipe Inference et Apprentissage

2.Laboratoire d'Informatique Universite de Tours

会议名称： National Conferences on Aritificial Intelligence

主办单位：

页码： 1945-1950

摘要： This paper introduces a new algorithm called SIAO1 for learning first order logic rules with genetic algorithms. SIAO1 uses the covering principle developed in AQ where seed examples are generalized into rules using however a genetic search, as initially introduced in the SIA algorithm for attribute-based representation. The genetic algorithm uses a high level representation for learning rules in first order logic and may deal with numerical data as well as background knowledge such as hierarchies over the predicates or tree structured values. The genetic operators may for instance change a predicate into a more general one according to background knowledge, or change a constant into a variable. The evaluation function may take into account user preference biases.

分类号： TP18-53