Recent advances in evolutionary computation

被引:90
作者
Yao, X [1 ]
Xu, Y
机构
[1] Univ Sci & Technol China, Nat Inspired Computat & Applicat Lab, Hefei 230027, Peoples R China
[2] Univ Birmingham, Sch Comp Sci, CERCIA, Birmingham B15 2TT, W Midlands, England
关键词
evolutionary computation; neural network ensemble; prisoner's dilemma; real-world application; computational time complexity;
D O I
10.1007/s11390-006-0001-4
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Evolutionary computation has experienced a tremendous growth in the last decade in both theoretical analyses and industrial applications. Its scope has evolved beyond its original meaning of "biological evolution" toward a wide variety of nature inspired computational algorithms and techniques, including evolutionary, neural, ecological, social and economical computation, etc., in a unified framework. Many research topics in evolutionary computation nowadays are not necessarily "evolutionary". This paper provides an overview of some recent advances in evolutionary computation that have been made in CERCIA at the University of Birmingham, UK. It covers a wide range of topics in optimization, learning and design using evolutionary approaches and techniques, and theoretical results in the computational time complexity of evolutionary algorithms. Some issues related to future development of evolutionary computation are also discussed.
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页码:1 / 18
页数:18
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