Internal Guidance for Satallax
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Abstract (arXiv)
We propose a new internal guidance method for automated theorem provers based on the given-clause algorithm. Our method influences the choice of unprocessed clauses using positive and negative examples from previous proofs. To this end, we present an efficient scheme for Naive Bayesian classification by generalising label occurrences to types with monoid structure. This makes it possible to extend existing fast classifiers, which consider only positive examples, with negative ones. We implement the method in the higher-order logic prover Satallax, where we modify the delay with which propositions are processed. We evaluated our method on a simply-typed higher-order logic version of the Flyspeck project, where it solves 26% more problems than Satallax without internal guidance.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 30 May 2016.
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Citing papers per year: 2022: 1.
1 paper.
- 2022Adversarial Learning to Reason in an Arbitrary Logiccited by 1
- 2022Adversarial Learning to Reason in an Arbitrary Logic6 Apr 2022