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首页> 外文期刊>計測自動制御学会論文集 >Network structure oriented evolutionary model: genetic network programming - its comparison with genetic programming
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Network structure oriented evolutionary model: genetic network programming - its comparison with genetic programming

机译:网络结构面向演化模型:基因网络编程 - 其与遗传编程的比较

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摘要

Recently many studies have been made on automatic design of complex systems by using evolutionary optimization techniques such as Genetic Algorithm (GA), Genetic Programming (GP) and Evolutionary Programming (EP). In this paper, a new method named Genetic Network Programming (GNP) is proposed in order to develop a more effective evolutionary optimization technique. GNP is composed of plural nodes which execute simple judgement/processing and they are connected with each other. To put it another way, GNP forms network structures, while general GPs form tree structures. This paper shows the detailed description about GNP and points out the differences among GNP, GP and other conventional graph based methods. The comparison between GNP and GP is also shown by using a virtual simulation, the tileworld.
机译:最近,通过使用遗传算法(GA),遗传编程(GP)和进化编程(EP)等进化优化技术,已经在复杂系统的自动设计上进行了许多研究。 在本文中,提出了一种名为遗传网络编程(GNP)的新方法,以便开发更有效的进化优化技术。 GNP由多个节点组成,该节点执行简单判断/处理,并且它们彼此连接。 将其另一种方式,GNP形成网络结构,而GEPS形成树结构。 本文显示了关于GNP的详细描述,并指出了GNP,GP和其他基于曲线图的方法之间的差异。 通过使用虚拟仿真,TileWorld也显示了GNP和GP之间的比较。

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