From the String Landscape to the Mathematical Landscape: a Machine-Learning Outlook

TL;DR

This paper reviews how machine learning is used to explore mathematical problems, aiding in conjecture formulation, pattern recognition, and computation, offering a complementary approach to traditional automated theorem proving.

Contribution

It introduces a machine-learning framework for exploring mathematical landscapes, emphasizing its role in enhancing human intuition and problem-solving.

Findings

AI assists in conjecture formulation

Machine learning helps recognize mathematical patterns

AI supports computational exploration in mathematics

Abstract

We review the recent programme of using machine-learning to explore the landscape of mathematical problems. With this paradigm as a model for human intuition - complementary to and in contrast with the more formalistic approach of automated theorem proving - we highlight some experiments on how AI helps with conjecture formulation, pattern recognition and computation.