I’m trying to convert a mathematical proof into Lean code and looking for the best ways to do this. I’ve been testing out AI coding helpers and standard math libraries to assist with the formalization process.
Has anyone had good experiences with using these automated tools for proofs in Lean? I’m curious about how effective these AI tools are for mathematical reasoning and if the standard definitions are good enough for more complicated proofs.
What has your experience been with this method? Are there any pitfalls or helpful tips on merging AI help with formal verification? I want to ensure I’m not overlooking any crucial parts of the formalization process.
Any suggestions for improving efficiency would be appreciated. Thanks!
Having delved into Lean for a significant period, I’ve found the utility of AI tools lies in their ability to assist rather than replace human input. Relying solely on AI often leads to misleading or incorrect results, as it may generate outputs that seem correct but fail in context.
An effective strategy I’ve adopted is drafting the proof outlines on my own, subsequently leveraging AI for repetitive parts or to enhance certain tactics. It’s crucial to grasp the standard libraries thoroughly to accurately interpret AI recommendations.
Moreover, I’ve experienced instances where AI introduces non-existent lemmas or outdated syntax. Thus, thorough checks of outputs are essential to ensure they fulfill your proof requirements. To streamline your process, maintaining a repository of verified proof templates can be incredibly beneficial.