Info-Evo：使用信息几何指导进化程序学习
Info-Evo: Using Information Geometry to Guide Evolutionary Program Learning
摘要：
描述了一种新的优化策略，信息Evo，其中使用非参数Fisher信息的自然梯度搜索被用来为进化学习算法提供持续的指导，使得进化过程优先地根据自然梯度在被识别为“最短路径”的方向上移动。一些具体的应用这种方法来自动化程序学习的审查，包括一个战略集成到MOSES程序学习框架的信息Evo。
英文摘要：
A novel optimization strategy, Info-Evo, is described, in which natural gradient search using nonparametric Fisher information is used to provide ongoing guidance to an evolutionary learning algorithm, so that the evolutionary process preferentially moves in the directions identified as "shortest paths" according to the natural gradient. Some specifics regarding the application of this approach to automated program learning are reviewed, including a strategy for integrating Info-Evo into the MOSES program learning framework.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
