Typed meta-interpretive learning of logic programs

Meta-interpretive learning (MIL) is a form of inductive logic programming that learns logic programs from background knowledge and examples. We claim that adding types to MIL can improve learning performance. We show that type checking can reduce the MIL hypothesis space by a cubic factor. We introd...

Täydet tiedot

Bibliografiset tiedot
Päätekijät: Ong, C, Morel, R, Cropper, A
Aineistotyyppi: Conference item
Julkaistu: Department of Mathemathics and Computer Science, University of Calabria 2019