Conjecture Refuting Algorithm

Conjecture refutation algorithms aim to automatically disprove mathematical conjectures by searching for counterexamples. Current research focuses on developing and improving these algorithms, employing techniques like Monte Carlo tree search, Bayesian learning, and large language models integrated with theorem provers to generate and evaluate conjectures across various mathematical domains, particularly graph theory. These advancements enhance the efficiency of mathematical exploration, accelerating the process of verifying or refuting hypotheses and potentially leading to new mathematical discoveries. The ultimate goal is to create powerful tools that assist mathematicians in tackling complex problems and expanding the boundaries of mathematical knowledge.