mlsanityData to 14 Oct 2026

Regularization in Spider-Style Strategy Discovery and Schedule Construction

arXiv 2403.12869 ↗First posted 19 Mar 2024cs.AI cs.LOcited by 2

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Abstract (arXiv)

To achieve the best performance, automatic theorem provers often rely on schedules of diverse proving strategies to be tried out (either sequentially or in parallel) on a given problem. In this paper, we report on a large-scale experiment with discovering strategies for the Vampire prover, targeting the FOF fragment of the TPTP library and constructing a schedule for it, based on the ideas of Andrei Voronkov's system Spider. We examine the process from various angles, discuss the difficulty (or ease) of obtaining a strong Vampire schedule for the CASC competition, and establish how well a schedule can be expected to generalize to unseen problems and what factors influence this property.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 6 of its 41 references that are in the map. First posted on arXiv 19 Mar 2024.

Builds on

6 of 41 references.

References · 6

  1. 2021SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimizationcited by 230
  2. 2014ParamILS: An Automatic Algorithm Configuration Frameworkcited by 89
  3. 2022A Survey of Methods for Automated Algorithm Configurationcited by 30
  4. 2023MizAR 60 for Mizar 50cited by 6
  5. 2016BliStrTune: Hierarchical Invention of Theorem Proving Strategiescited by 5
  6. 2013MaLeS: A Framework for Automatic Tuning of Automated Theorem Proverscited by 3

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Citing papers per year: 2024: 1; 2025: 1.

2 papers.