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A Dynamic Programming Approach to Individual Initialization in Genetic Programming

机译:基因编程中的各个初始化的动态编程方法

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In this paper we present a new initialization method for genetic programming based on randomized exhaustive enumeration. It naturally enables complete sharing of sub trees among individuals which in turn allows an efficient reuse of computations. Moreover, it can be implemented as a random one pass initialization. We present experimental results on different instances of simple symbolic regression exploring the landscape of possible initializations based on our approach and confirming the usability of these initializations.
机译:本文介绍了一种基于随机详尽枚举的遗传编程的新初始化方法。它自然能够在个人中完全共享子树,这反过来允许有效地重用计算。此外,它可以实现为随机初始化。我们对不同实例的简单符号回归实例提出了探索可能的初始化景观的实验结果,并确认了这些初始化的可用性。

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