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.

翻译：OpenTensor是对AlphaTensor的复现，后者通过深度强化学习（DRL）发现了一种超越现有最优方法的矩阵乘法新算法。尽管AlphaTensor为解决科学问题提供了一个有前景的框架，但由于其使用了大量技巧且缺乏源代码，实际复现极为困难。本文中，我们清理了算法流程，明确了技术细节，并对训练过程进行了若干改进。计算结果表明，OpenTensor能够成功找到高效的矩阵乘法算法。