遗传编程中下游学习器对程序非线性演化的影响

1. 12:00
   arXiv · Neural and Evolutionary Computing

   遗传编程中下游学习器如何重塑程序需演化的非线性

   研究将遗传编程程序作为下游学习器的输入，在布尔域中以 Fourier degree 1 到 6 调控目标非线性。线性学习器迫使演化程序精确达到目标 degree，30 次运行无一例外；树集成则用更简单程序、成功率高 4 倍。演化程序 degree 可作为运行期免费诊断指标，但学习器越强，程序可读性越低。

Current heat 9·Comparable peak 10（Oct 8）·Comparable change over 24 hours –

The trend compares only the same participants observed continuously; its range may be smaller than the current heat count. Move or click on the chart to inspect hourly heat; use the left and right arrow keys to switch.