We study both genotypic and phenotypic convergence in GP floating point continuous domain symbolic regression over thousands of generations. Subtree fitness variation across the population is measured and shown in many cases to fall. In an expanding region about the root node, both genetic opcodes and function evaluation values are identical or nearly identical. Bottom up (leaf to root) analysis shows both syntactic and semantic (including entropy) similarity expand from the outermost node. Despite large regions of zero variation, fitness continues to evolve and near zero crossover disruption suggests improved GP systems within existing memory use.

中文翻译：

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遗传编程收敛

我们研究了数千代 GP 浮点连续域符号回归中的基因型和表型收敛性。整个种群的子树适应度变化被测量并在许多情况下显示下降。在围绕根节点的扩展区域中，遗传操作码和函数评估值相同或几乎相同。自下而上（叶到根）分析显示句法和语义（包括熵）相似性从最外层节点扩展。尽管零变化的大区域，适应度继续发展，接近零交叉中断表明在现有内存使用中改进了 GP 系统。