English

Learning Algebraic Structures: Preliminary Investigations

Machine Learning 2019-05-20 v1 High Energy Physics - Theory Group Theory Rings and Algebras Machine Learning

Abstract

We employ techniques of machine-learning, exemplified by support vector machines and neural classifiers, to initiate the study of whether AI can "learn" algebraic structures. Using finite groups and finite rings as a concrete playground, we find that questions such as identification of simple groups by "looking" at the Cayley table or correctly matching addition and multiplication tables for finite rings can, at least for structures of small size, be performed by the AI, even after having been trained only on small number of cases. These results are in tandem with recent investigations on whether AI can solve certain classes of problems in algebraic geometry.

Keywords

Cite

@article{arxiv.1905.02263,
  title  = {Learning Algebraic Structures: Preliminary Investigations},
  author = {Yang-Hui He and Minhyong Kim},
  journal= {arXiv preprint arXiv:1905.02263},
  year   = {2019}
}

Comments

26 pages, 4 figures

R2 v1 2026-06-23T08:58:36.228Z