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arXiv · 2109.07132

Parallel Constraint-Driven Inductive Logic Programming

Andrew Cropper·Oghenejokpeme Orhobor·Cristian Dinu·Rolf Morel
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Abstract

Multi-core machines are ubiquitous. However, most inductive logic programming (ILP) approaches use only a single core, which severely limits their scalability. To address this limitation, we introduce parallel techniques based on constraint-driven ILP where the goal is to accumulate constraints to restrict the hypothesis space. Our experiments on two domains (program synthesis and inductive general game playing) show that (i) parallelisation can substantially reduce learning times, and (ii) worker communication (i.e. sharing constraints) is important for good performance.

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Andrew Cropper, Oghenejokpeme Orhobor, Cristian Dinu, Rolf Morel. 2021-09-15. Parallel Constraint-Driven Inductive Logic Programming. https://arxiv.org/abs/2109.07132

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