Visualizing the loss of diversity in genetic programming

被引：17

作者：

Daida, JM ^{[1
]}

Ward, DJ ^{[1
]}

Hilss, AM ^{[1
]}

Long, SL ^{[1
]}

Hodges, MR ^{[1
]}

Kriesel, JT ^{[1
]}

机构：

[1] Ctr Study Complex Syst, Ann Arbor, MI 48109 USA

来源：

CEC2004: PROCEEDINGS OF THE 2004 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2 | 2004年

关键词：

D O I：

10.1109/CEC.2004.1331037

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper introduces visualization techniques that allow for a multivariate approach in understanding the dynamics that underlie genetic programming (GP). Emphasis is given toward understanding the relationship between problem difficulty and the loss of diversity. The visualizations raise questions about diversity and problem solving efficacy, as well as the role of the initial population in determining solution outcomes.

引用

页码：1225 / 1232

页数：8

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