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General Schema Theory for Genetic Programming with Subtree-Swapping Crossover: Part II

机译:具有子树交换交叉的遗传程序设计的一般模式理论:第二部分

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This paper is the second part of a two-part paper which introduces a general schema theory for genetic programming (GP) with subtree-swapping crossover (Part I (Poli and McPhee, 2003)). Like other recent GP schema theory results, the theory gives an exact formulation (rather than a lower bound) for the expected number of instances of a schema at the next generation. The theory is based on a Cartesian node reference system, introduced in Part I, and on the notion of a variable-arity hyperschema, introduced here, which generalises previous definitions of a schema. The theory includes two main theorems describing the propagation of GP schemata: a microscopic and a macroscopic schema theorem. The microscopic version is applicable to crossover operators which replace a subtree in one parent with a subtree from the other parent to produce the offspring. Therefore, this theorem is applicable to Koza's GP crossover with and without uniform selection of the crossover points, as well as one-point crossover, size-fair crossover, strongly-typed GP crossover, context-preserving crossover and many others. The macroscopic version is applicable to crossover operators in which the probability of selecting any two crossover points in the parents depends only on the parents' size and shape. In the paper we provide examples, we show how the theory can be specialised to specific crossover operators and we illustrate how it can be used to derive other general results. These include an exact definition of effective fitness and a size-evolution equation for GP with subtree-swapping crossover.
机译:本文是由两部分组成的论文的第二部分,该论文介绍了带有子树交换交叉的遗传规划(GP)的通用模式理论(第一部分(Poli和McPhee,2003年))。像其他最近的GP模式理论结果一样,该理论为下一代模式的预期实例数给出了精确的表述(而不是下限)。该理论基于在第一部分中介绍的笛卡尔节点参考系统,以及在此介绍的可变域超模式的概念,该概念概括了模式的先前定义。该理论包括两个描述GP图式传播的主要定理:微观和宏观图式定理。微观版本适用于交叉运算符,该运算符将一个父级中的子树替换为另一父级中的子树以产生后代。因此,该定理适用于有或没有统一选择交叉点的Koza GP交叉点,以及单点交叉,大小公平的交叉点,强类型的GP交叉点,上下文保留的交叉点等。宏观版本适用于交叉运算符,其中选择父级中任意两个交叉点的可能性仅取决于父级的大小和形状。在本文中,我们提供了示例,说明了该理论如何专门用于特定的交叉算子,并说明了如何将其用于得出其他一般结果。这些包括有效适应度的精确定义和带有子树交换交叉的GP的大小演化方程。

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