SAT-Based PAC Learning of Description Logic Concepts

• URL: http://arxiv.org/abs/2305.08511v1
• Date: Mon, 15 May 2023 10:20:31 GMT
• Title: SAT-Based PAC Learning of Description Logic Concepts
• Authors: Balder ten Cate, Maurice Funk, Jean Christoph Jung, Carsten Lutz
• Abstract summary: We propose bounded fitting as a scheme for learning logic concepts in the presence of description. We present the system SPELL which implements bounded fitting for the description logic $mathcalELHr$ based on a SAT solver, and compare its performance to a state-of-the-art learner.
• Score: 18.851061569487616
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose bounded fitting as a scheme for learning description logic concepts in the presence of ontologies. A main advantage is that the resulting learning algorithms come with theoretical guarantees regarding their generalization to unseen examples in the sense of PAC learning. We prove that, in contrast, several other natural learning algorithms fail to provide such guarantees. As a further contribution, we present the system SPELL which efficiently implements bounded fitting for the description logic $\mathcal{ELH}^r$ based on a SAT solver, and compare its performance to a state-of-the-art learner.

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