A genetic approach to the truck backer upper problem and the inter-twined spiral problem

J. Koza
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引用次数: 82

Abstract

The author describes a biologically motivated paradigm, genetic programming, which can solve a variety of problems. When genetic programming solves a problem, it produces a computer program that takes the state variables of the system as input and produces the actions required to solve the problem as output. Genetic programming is explained and applied to two well-known benchmark problems from the field of neural networks. The truck backer upper problem is a multidimensional control problem and the inter-twined spirals problem is a challenging classification problem.<>
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基于遗传算法的卡车后轮上部问题和缠绕螺旋问题
作者描述了一个生物驱动的范例,遗传编程,它可以解决各种问题。当遗传编程解决一个问题时,它产生一个计算机程序,该程序将系统的状态变量作为输入,并产生解决问题所需的操作作为输出。本文解释了遗传规划,并将其应用于神经网络领域的两个著名的基准问题。卡车后部上部问题是一个多维控制问题,而缠绕螺旋问题是一个具有挑战性的分类问题。
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