An Orthogonal Cartesian Genetic Programming Algorithm for Evolvable Hardware

被引：3
|
作者：
Ni, Fuchuan [1 ,2 ]
Li, Yuanxiang [1 ]
Yang, Xiaoyan [1 ]
Ni, Fuchuan [1 ,2 ]
Xiang, Jinhai [2 ]
机构：
[1] Wuhan Univ, State Key Lab Software Engn, Wuhan, Peoples R China
[2] Huazhong Agr Univ, Dept Comp Sci, Coll Informat, Wuhan, Peoples R China
来源：
2014 INTERNATIONAL CONFERENCE ON IDENTIFICATION, INFORMATION AND KNOWLEDGE IN THE INTERNET OF THINGS (IIKI 2014) | 2014年
关键词：
Evolvable hardware; Cartesian Genetic Programming; orthogonal experiment design; Evolutionary algorithm; CHALLENGES;
D O I：
10.1109/IIKI.2014.52
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Evolvable hardware (EHW) is facing the problems of scalability. Evolutionary algorithms often trap into local optima, or stalling in the later procedure. This paper analyses the difficulty of EHW. To improve the efficiency of Cartesian Genetic Programming (CGP), Neighborhood searching and orthogonal experiment design are tailed to an orthogonal mutation operator and a new Orthogonal Cartesian Genetic Programming algorithm is proposed. Demonstrated by experiments on the benchmark, the proposed Orthogonal Cartesian Genetic Programming can jump out of Local optima and decrease the stalling effect.
引用
收藏
页码：220 / 224
页数：5
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