Towards Machine Learning Induction
Logic in Computer Science
2019-03-27 v2 Machine Learning
Abstract
Induction lies at the heart of mathematics and computer science. However, automated theorem proving of inductive problems is still limited in its power. In this abstract, we first summarize our progress in automating inductive theorem proving for Isabelle/HOL. Then, we present MeLoId, our approach to suggesting promising applications of induction without completing a proof search.
Cite
@article{arxiv.1812.04088,
title = {Towards Machine Learning Induction},
author = {Yutaka Nagashima},
journal= {arXiv preprint arXiv:1812.04088},
year = {2019}
}
Comments
This abstract is submitted to the fourth Conference on Artificial Intelligence (AITP2019) and Theorem Proving and to the third Workshop on Learning in Verification (LiVE2019)