Advancing mathematics by guiding human intuition with AI

A framework through which machine learning can guide mathematicians in discovering new conjectures and theorems is presented and shown to yield mathematical insight on important open problems in different areas of pure mathematics. The practice of mathematics involves discovering patterns and using these to formulate and prove conjectures, resulting in theorems. Since the 1960s, mathematicians have used computers to assist in the discovery of patterns and formulation of conjectures(1), most famously in the Birch and Swinnerton-Dyer conjecture(2), a Millennium Prize Problem(3). Here we provide examples of new fundamental results in pure mathematics that have been discovered with the assistance of machine learning-demonstrating a method by which machine learning can aid mathematicians in discovering new conjectures and theorems. We propose a process of using machine learning to discover potential patterns and relations between mathematical objects, understanding them with attribution techniques and using these observations to guide intuition and propose conjectures. We outline this machine-learning-guided framework and demonstrate its successful application to current research questions in distinct areas of pure mathematics, in each case showing how it led to meaningful mathematical contributions on important open problems: a new connection between the algebraic and geometric structure of knots, and a candidate algorithm predicted by the combinatorial invariance conjecture for symmetric groups(4). Our work may serve as a model for collaboration between the fields of mathematics and artificial intelligence (AI) that can achieve surprising results by leveraging the respective strengths of mathematicians and machine learning.

Automated summary

This study demonstrates the application of machine learning in assisting mathematicians to discover new conjectures and theorems, providing examples of new fundamental results in pure mathematics. It outlines a process of using machine learning to discover potential patterns and relations between mathematical objects, guiding intuition and proposing conjectures. Leveraging strengths of mathematicians and machine learning can lead to surprising results in the collaboration between mathematics and artificial intelligence.