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GeoILP: A Synthetic Dataset to Guide Large-Scale Rule Induction
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Introduces GeoILP, a synthetic dataset of geometric-style rule induction tasks to benchmark and guide large-scale inductive logic programming systems.
Problem
Existing inductive logic programming (ILP) systems handle only small-scale tasks, large-scale applications with varied language biases are rarely explored, and most systems require expert-defined language bias.
Approach
A synthetic dataset designed to test and guide ILP rule induction at large scale across different language biases, intended to reduce reliance on expert-defined language bias.
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