First Experiments with Neural cvc5

14 pages•Published: May 26, 2024

Jelle Piepenbrock, Mikolas Janota, Josef Urban and Jan Jakubův

Abstract

The cvc5 solver is today one of the strongest systems for solving first order problems with theories but also without them. In this work we equip its enumeration-based instan- tiation with a neural network that guides the choice of the quantified formulas and their instances. For that we develop a relatively fast graph neural network that repeatedly scores all available instantiation options with respect to the available formulas. The network runs directly on a CPU without the need for any special hardware. We train the neural guidance on a large set of proofs generated by the e-matching instantiation strategy and evaluate its performance on a set of previously unseen problems.

Keyphrases: automated reasoning, machine learning, theorem proving

In: Nikolaj Bjørner, Marijn Heule and Andrei Voronkov (editors). Proceedings of 25th Conference on Logic for Programming, Artificial Intelligence and Reasoning, vol 100, pages 264-277.

Links:	https://easychair.org/publications/paper/Z6b2
	https://doi.org/10.29007/h5dr

BibTeX entry

@inproceedings{LPAR2024:First_Experiments_with_Neural,
  author    = {Jelle Piepenbrock and Mikolas Janota and Josef Urban and Jan Jakubův},
  title     = {First Experiments with Neural cvc5},
  booktitle = {Proceedings of 25th Conference on Logic for Programming, Artificial Intelligence and Reasoning},
  editor    = {Nikolaj Bjørner and Marijn Heule and Andrei Voronkov},
  series    = {EPiC Series in Computing},
  volume    = {100},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/Z6b2},
  doi       = {10.29007/h5dr},
  pages     = {264-277},
  year      = {2024}}

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