Semantic Aware Crossover for Genetic Programming: The Case for Real-Valued Function Regression
Semantic Aware Crossover for Genetic Programming: The Case for Real-Valued Function Regression
复制标题
遗传编程的语义感知交叉：实值函数回归的案例
DOI：
--
复制
发表时间：
2009
期刊：
影响因子：
--
通讯作者：
M. O’Neill
中科院分区：
文献类型：
--
作者：
Nguyen Quang Uy;N. X. Hoai;M. O’Neill
在本文中，我们应用[2]中的思想，研究了一些基于语义的指导对GP的交叉算子的影响。我们进行了一系列的实值符号回归问题的家庭实验，检查四个不同的语义感知交叉算子。一个操作符考虑交换的子树的语义，而另一个操作符比较子树与它们的父树的语义。采用两个控制操作符，这颠倒了语义等价性测试的逻辑。结果表明，在测试问题的家庭检查，（近似）语义感知交叉算子可以提供性能优势，在遗传编程中采用的标准子树交叉。
In this paper, we apply the ideas from [2] to investigate the effect of some semantic based guidance to the crossover operator of GP. We conduct a series of experiments on a family of real-valued symbolic regression problems, examining four different semantic aware crossover operators. One operator considers the semantics of the exchanged subtrees, while the other compares the semantics of the child trees to their parents. Two control operators are adopted which reverse the logic of the semantic equivalence test. The results show that on the family of test problems examined, the (approximate) semantic aware crossover operators can provide performance advantages over the standard subtree crossover adopted in Genetic Programming.