Applications of automated reasoning in mathematics

2 PM, 2 Oct 2026

Alexei Lisitsa makes the case that in pure mathematics, where rigour and structure are central, symbolic methods in AI remain essential.

In the era of machine learning and LLMs, symbolic methods in AI—automated theorem proving and disproving, constraint solving, and SAT solving—get less attention, despite successes in mathematical problem solving. Dr Alexei Lisitsa explores how automated reasoning (AR) tools can produce new mathematical insights, and argues that in pure maths, where rigour and structure are central, symbolic AI remains essential.

Dr Alexei Lisitsa is a senior lecturer, and the director of postgraduate research, in the School of Computer Science and Informatics at the University of Liverpool. He works on applied automated reasoning, applied machine learning, and automated verification and security.

Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics
Applications of automated reasoning in mathematics