Machine Learning Guidance and Proof Certification for Connection Tableaux
Logic in Computer Science
2018-05-16 v3
Abstract
Connection calculi allow for very compact implementations of goal-directed proof search. We give an overview of our work related to connection tableaux calculi: First, we show optimised functional implementations of clausal and nonclausal proof search, including a consistent Skolemisation procedure for machine learning. Then, we show two guidance methods based on machine learning, namely reordering of proof steps with Naive Bayesian probablities, and expansion of a proof search tree with Monte Carlo Tree Search. Finally, we give a translation of connection proofs to LK, enabling proof certification and automatic proof search in interactive theorem provers.
Cite
@article{arxiv.1805.03107,
title = {Machine Learning Guidance and Proof Certification for Connection Tableaux},
author = {Michael Färber and Cezary Kaliszyk and Josef Urban},
journal= {arXiv preprint arXiv:1805.03107},
year = {2018}
}
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