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Adaptive Bayesian logic programs. (English) Zbl 1006.68504
Rouveirol, Céline (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, 104-117 (2001).
Summary: First order probabilistic logics combine a first order logic with a probabilistic knowledge representation. In this context, we introduce continuous Bayesian logic programs, which extend the recently introduced Bayesian logic programs to deal with continuous random variables. Bayesian logic programs tightly integrate definite logic programs with Bayesian networks. The resulting framework nicely seperates the qualitative (i.e. logical) component from the quantitative (i.e. the probabilistic) one. We also show how the quantitative component can be learned using a gradient-based maximum likelihood method.
For the entire collection see [Zbl 0971.00030].

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