Symmetry breaking for inductive logic programming

TL;DR

This paper introduces a symmetry-breaking method for inductive logic programming implemented in answer set programming, significantly reducing hypothesis search time across various domains.

Contribution

It presents a novel symmetry-breaking technique for hypothesis space search in inductive logic programming, improving efficiency in answer set programming implementations.

Findings

Reduced solving times from over an hour to 17 seconds

Effective across multiple domains including visual reasoning and game playing

Demonstrates substantial efficiency gains in hypothesis search

Abstract

The goal of inductive logic programming is to search for a hypothesis that generalises training data and background knowledge. The challenge is searching vast hypothesis spaces, which is exacerbated because many logically equivalent hypotheses exist. To address this challenge, we introduce a method to break symmetries in the hypothesis space. We implement our idea in answer set programming. Our experiments on multiple domains, including visual reasoning and game playing, show that our approach can reduce solving times from over an hour to just 17 seconds.