Holophrasm: a neural Automated Theorem Prover for higher-order logic
Daniel P.Z. Whalen Stanford University
Abstract
I propose a system for Automated Theorem Proving in higher order logic using deep learning and eschewing hand-constructed features. Holophrasm exploits the formalism of the Metamath language and explores partial proof trees using a neural-network-augmented bandit algorithm and a sequence-to-sequence model for action enumeration. The system proves 14% of its test theorems from Metamath’s set.mm module.
原文 arXiv:1608.02644;中英对照 + 大白话阅读 https://aha.fim.ai/paper/1608.02644v2