TL;DR提出了一种新的增强符号回归机 (RSRM) 模型,通过 Monte Carlo 树搜索、双 Q-learning 块和调制子树发现块,可以从极少的数据中学习复杂的数学方程,并取得了关于符号回归的最新性能记录。
Abstract
In nature, the behaviors of many complex systems can be described by
parsimonious math equations. Automatically distilling these equations from
limited data is cast as a symbolic regression process which hitherto remains a
grand challenge. Keen efforts in recent years have been placed