Genetic network programming with automatically generated variable size macro nodes
Genetic network programming with automatically generated variable size macro nodes
复制标题
使用自动生成的可变大小宏节点的遗传网络编程
DOI：
10.1109/cec.2004.1330929
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
Jinglu Hu
中科院分区：
文献类型：
--
作者：
Hiroshi Nakagoe;K. Hirasawa;Jinglu Hu
遗传网络规划（GNP）是遗传算法（GA）和遗传规划（GP）等进化计算的扩展，它以有向图结构作为基因。宏指令通常以子程序、函数局部化等形式引入，本文介绍了GNP中的宏指令结构--自动生成宏节点（AGM），它能有效地减少进化时间，并表明宏指令对获得良好的性能是有用的。但AGM具有固定的节点数，并且宏指令演化的有效性取决于主程序调用宏指令和初始化参数。因此，本文提出了一种新的变尺寸自适应陀螺仪，即变尺寸自适应陀螺仪，通过改变自适应陀螺仪的尺寸来进一步提高其性能。这是根据需要添加和删除节点的机制。在模拟中，GNP程序之间的比较，只有GNP与传统的AGM和GNP与可变尺寸的AGM进行使用瓷砖世界。仿真结果表明，该方法优于传统GNP和GNP与传统GM。同时阐明了新AGM得到的节点迁移规则是能够处理未知环境的通用规则。
Genetic network programming (GNP) has directed graph structures as genes, which is extended from other evolutionary computations such as genetic algorithm (GA) and genetic programming (GP). Generally, macroinstructions are introduced as sub-routines, function localization and so on. Previously, we have introduced the structure of macroinstructions in GNP named automatically generated macro nodes (AGMs) for reducing the time of evolution efficiently, and showed that macroinstructions are useful to acquire good performances. But the AGMs have fixed number of nodes, and it is found that the effectiveness of evolution of macroinstructions depends on the main program calling them and initialized parameters. Accordingly in this paper, new AGMs are introduced to improve their performances further more by the mechanism of varying the size of AGMs, which are named variable size AGMs. This is the mechanism to add and delete nodes according to necessity. In the simulations, comparisons between GNP program only, GNP with conventional AGMs and GNP with variable size AGMs are carried out using the tile world. Simulation results show that the proposed method is better compared with conventional GNP and GNP with conventional GMs. And also it is clarified that the node transition rules obtained by new AGMs show the generalized rules able to deal with unknown environments.
可变大小遗传网络编程
DOI：
--
发表时间：
2003
期刊：
Trans.IEE of Japan Vol.123-C, No.3
影响因子：
--
作者：
H.Katagiri;K.Hirasawa;H.Jinglu;J.Murata
通讯作者：
J.Murata