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. Students interested in participating in this project should have a strong foundation in mathematics, particularly in discrete mathematics and graph theory. Familiarity with machine learning concepts and experience with programming languages such as Python are essential. Knowledge of deep learning frameworks like PyTorch or TensorFlow will be beneficial, as the project involves implementing machine learning models to test various conjectures. Additionally, students should be comfortable with exploring new AI techniques and willing to engage in collaborative research efforts that bridge multiple disciplines. Enthusiasm for mathematical discovery and problem-solving using computational methods will be key to successfully contributing to this groundbreaking initiative.
This project will run for 10 weeks, vs the regular 8-week Math+ program. Participants will be compensated the same as Data+ participants.
Project Manager: Fan Wei
