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...
| Main Authors: | , , |
|---|---|
| Format: | Conference item |
| Izdano: |
Department of Mathemathics and Computer Science, University of Calabria
2019
|