• Corpus ID: 231861802

Learning Equational Theorem Proving

@article{Piepenbrock2021LearningET,
  title={Learning Equational Theorem Proving},
  author={Jelle Piepenbrock and Tom M. Heskes and Mikol'avs Janota and Josef Urban},
  journal={ArXiv},
  year={2021},
  volume={abs/2102.05547}
}
We develop Stratified Shortest Solution Imitation Learning (3SIL) to learn equational theorem proving in a deep reinforcement learning (RL) setting. The self-trained models achieve state-of-the-art performance in proving problems generated by one of the top open conjectures in quasigroup theory, the Abelian Inner Mapping (AIM) Conjecture. To develop the methods, we first use two simpler arithmetic rewriting tasks that share tree-structured proof states and sparse rewards with the AIM problems… 

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