  OpenTensor is a reproduction of AlphaTensor, which discovered a new algorithm
that outperforms the state-of-the-art methods for matrix multiplication by Deep
Reinforcement Learning (DRL). While AlphaTensor provides a promising framework
for solving scientific problems, it is really hard to reproduce due to the
massive tricks and lack of source codes. In this paper, we clean up the
algorithm pipeline, clarify the technical details, and make some improvements
to the training process. Computational results show that OpenTensor can
successfully find efficient matrix multiplication algorithms.
