This is an innovative project that explores the intersection of artificial intelligence and mathematics. This initiative aims to leverage AI’s capabilities in pattern recognition and exhaustive search to tackle complex problems in discrete mathematics, such as finding counterexamples to open conjectures. By framing these mathematical challenges as computational problems, students will utilize machine learning models, including reinforcement learning and graph neural networks, to efficiently explore vast mathematical spaces. This approach not only accelerates mathematical discovery by potentially uncovering new patterns and insights but also complements human intuition and creativity, driving forward the resolution of long-standing open questions in fields like graph theory and game theory.
This project offers a unique opportunity for students to engage with cutting-edge developments in AI and its applications to abstract mathematical domains. Participants will collaboratively develop a framework that mathematicians can use to explore conjectures and gain insights, even when formal proofs remain elusive. By working on this project, students will contribute to the development of AI techniques while gaining valuable experience in both theoretical and applied aspects of these fields.
Project Lead: Fan Wei, Mathematics
View the team’s final posters here:
AI_Powered_Discovery_of_Counterexamples_Poster_1
AI_Powered_Discovery_of_Counterexamples_Poster_2
The students created 2 videos over the summer describing their work. Watch below:
