深度优先的多基因表达式程序设计  

Multi-Gene Expression Programming with Depth-First Decoding Principle

作　　者：邓薇[1] 何锫[1,2] 钱俊彦[3] 

机构地区：[1]长沙理工大学计算机与通信工程学院长沙410114 [2]北京大学高可信软件技术教育部重点实验室北京100871 [3]桂林电子科技大学广西可信软件重点实验室桂林541004

出　　处：《模式识别与人工智能》2013年第9期819-828,共10页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.61170199,61063002);湖南省教育厅重点资助科研项目(No.11A004);湖南省研究生科研创新项目(No.CX2012B367);广西可信软件重点实验室项目(No.KX201208)资助

摘　　要：基因表达式程序设计(GEP)是应用十分广泛的自动程序设计方法.就解码方法而言,它主要依据广度优先原则来实施从个体表示到表达式的转换.这代表基因片段的含义会因环境的变化而变化.为此,现有GEP对个体的评估缺乏并发支持能力.本文从理论与实验两个方面证实:深度优先原则及个体多解技术,即让单个染色体编码多个解的技术,既可解决以上GEP困境也可显著改善其性能.Gene expression programming （GEP） is an automatic programming approach which is widely used in many areas. As far as the decoding method is concerned, it uses the breadth-first principle to transform individuals into expressions. It means that the meaning ~f a gene segment will change with the context. Consequently, any individual can not be concurrently evaluated in most existing GEPs. In this paper, the theoretical analysis and experiments show that the depth-first principle as well as multi-solution techniques, i.e. techniques for encoding of multiple solutions into a single chromosome, can not only solve the mentioned GEP problem, but also significantly improve its performance.

关 键 词：演化计算 遗传程序设计 基因表达式程序设计 多表达式程序设计 符号回归 

分 类 号：TP311.11[自动化与计算机技术—计算机软件与理论]