Symmetry breaking for inductive logic programming
Fuente:
arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866911392826654720 |
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| author | Cropper, Andrew Cerna, David M. Järvisalo, Matti |
| author_facet | Cropper, Andrew Cerna, David M. Järvisalo, Matti |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_06263 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Symmetry breaking for inductive logic programming Cropper, Andrew Cerna, David M. Järvisalo, Matti Artificial Intelligence Machine Learning 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. |
| title | Symmetry breaking for inductive logic programming |
| topic | Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2508.06263 |