Curiosity-driven RL for symbolic equation solving

Kevin P. O'Keeffe
10/19/2025
cs.LGcs.AI

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Abstract

We explore if RL can be useful for symbolic mathematics. Previous work showed contrastive learning can solve linear equations in one variable. We show model-free PPO \cite{schulman2017proximal} augmented with curiosity-based exploration and graph-based actions can solve nonlinear equations such as those involving radicals, exponentials, and trig functions. Our work suggests curiosity-based exploration may be useful for general symbolic reasoning tasks.

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Cite this paper

@article{okeeffe2025curiositydriven,
  title  = {Curiosity-driven RL for symbolic equation solving},
  author = {Kevin P. O'Keeffe},
  year   = {2025},
  eprint = {2510.17022},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.17022v2}
}

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