We study multiple predicate learning in an empirical setting. Problems with existing inductive logic programming approaches in this setting are sketched and an empirical ILP syste...
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Inductive Logic Programming (ILP) systems have been successfully applied to solve complex problems in bioinformatics by viewing them as binary classification tasks. It remains an...
Huma Lodhi, Stephen Muggleton, Michael J. E. Stern...
While existing learning techniques can be viewed as inducing programs from examples, most research has focused on rather narrow classes of programs, e.g., decision trees or logic ...
Intelligent agents must be able to handle the complexity and uncertainty of the real world. Logical AI has focused mainly on the former, and statistical AI on the latter. Markov l...
Pedro Domingos, Stanley Kok, Hoifung Poon, Matthew...