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Towards combining inductive logic programming with Bayesian networks. (English) Zbl 1006.68518
Rouveirol, CĂ©line (ed.) et al., Inductive logic programming. 11th international conference, ILP 2001, Strasbourg, France, September 9-11, 2001. Proceedings. Berlin: Springer. Lect. Notes Comput. Sci. 2157, 118-131 (2001).
Summary: Recently, new representation languages that integrate first order logic with Bayesian networks have been developed. Bayesian logic programs are one of these languages. In this paper, we present results on combining Inductive Logic Programming (ILP) with Bayesian networks to learn both the qualitative and the quantitative components of Bayesian logic programs. More precisely, we show how to combine the ILP setting learning from interpretations with score-based techniques for learning Bayesian networks. Thus, the paper positively answers Koller and Pfeffer’s question, whether techniques from ILP could help to learn the logical component of first order probabilistic models.
For the entire collection see [Zbl 0971.00030].

MSC:
68N17 Logic programming
68T05 Learning and adaptive systems in artificial intelligence
Software:
BNT
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