Learning logic programs through divide, constrain, and conquer

2021/09/16 by Andrew Cropper, Cropper, Andrew
Computer Science · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Games #FOS: Computer and information sciences #Logic, Reasoning, and Knowledge #Logic, programming, and type systems #Machine Learning (cs.LG)

paper · pdf · doi:10.48550/arxiv.2109.07818

openalex publication_date 2021/09/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We introduce an inductive logic programming approach that combines classical divide-and-conquer search with modern constraint-driven search. Our anytime approach can learn optimal, recursive, and large programs and supports predicate invention. Our experiments on three domains (classification, inductive general game playing, and program synthesis) show that our approach can increase predictive accuracies and reduce learning times.

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