HyperTree Proof Search for Neural Theorem Proving

05/23/2022

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by   Guillaume Lample, et al.

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We propose an online training procedure for a transformer-based automated theorem prover. Our approach leverages a new search algorithm, HyperTree Proof Search (HTPS), inspired by the recent success of AlphaZero. Our model learns from previous proof searches through online training, allowing it to generalize to domains far from the training distribution. We report detailed ablations of our pipeline's main components by studying performance on three environments of increasing complexity. In particular, we show that with HTPS alone, a model trained on annotated proofs manages to prove 65.4 Metamath theorems, significantly outperforming the previous state of the art of 56.5 to 82.6 on the Lean-based miniF2F-curriculum dataset from 31