Flattening and saturation: Two representation changes for generalization

DOI10.1023/A:1022678217288zbMath0804.68024OpenAlexW1946621657MaRDI QIDQ1326585

Céline Rouveirol

Publication date: 12 January 1995

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1022678217288

zbMATH Keywords

inductive logic programminggeneralization with background knowledge

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Logic programming (68N17)

Related Items (8)

Nonmonotonic abductive inductive learning ⋮ First-order \(jk\)-clausal theories are PAC-learnable ⋮ Logical approximation for program analysis ⋮ Inductive constraint logic ⋮ Construction and learnability of canonical Horn formulas ⋮ Defining behaviorizeable relations to enable inference in semi-automatic program synthesis ⋮ Partial Functions and Equality in Answer Set Programming ⋮ Meta-interpretive learning as metarule specialisation

This page was built for publication: Flattening and saturation: Two representation changes for generalization