Evolving Distributed Algorithms with Genetic Programming: Election

被引：0
|
作者：
Weise, Thomas [1 ]
Zapf, Michael [1 ]
机构：
[1] Univ Kassel, Distributed Syst Grp, D-34121 Kassel, Germany
来源：
WORLD SUMMIT ON GENETIC AND EVOLUTIONARY COMPUTATION (GEC 09) | 2009年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we present a detailed analysis of the application of Genetic Programming to the evolution of distributed algorithms. This research field has many facets which make it especially difficult. These aspects are discussed and countermeasures are provided. Six different Genetic Programming approaches (SGP, eSGP, LGP, RBGP, eRBGP, and Fraglets) are applied to the election problem as case study utilizing these countermeasures. The results of the experiments are analyzed statistically and discussed thoroughly.
引用
收藏
页码：577 / 584
页数：8
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