Stochastically searching the space of candidate clauses is an appealing way to scale up ILP to large datasets. We address an approach that uses a Bayesian network model to adaptive...
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
One challenge faced by many Inductive Logic Programming (ILP) systems is poor scalability to problems with large search spaces and many examples. Randomized search methods such as ...
Developing dialogue systems is a complex process. In particular, designing efficient dialogue management strategies is often difficult as there are no precise guidelines to develo...
This paper presents and evaluates an approach to Bayesian model averaging where the models are Bayesian nets (BNs). Prior distributions are defined using stochastic logic programs...