DocumentCode
395582
Title
Immune, swarm, and evolutionary algorithms. Part II: philosophical comparisons
Author
De Castro, Leandro Nunes
Author_Institution
Comput. & Electr. Eng. Sch., State Univ. of Campinas, Brazil
Volume
3
fYear
2002
fDate
18-22 Nov. 2002
Firstpage
1469
Abstract
For Part I see ibid. vol. 3 (2002). In the first part of this paper, the standard evolutionary, immune, and swarm algorithms were reviewed. This second part starts by presenting a philosophical discussion about some similarities and differences among the various approaches in terms of their basic components, structure, knowledge storage, adaptation paradigm, interactions, and metaphor. Then, the identification of the main features of each technique is performed in order to shed some light into how to create hybrid algorithms.
Keywords
artificial intelligence; genetic algorithms; multi-agent systems; adaptation paradigm; evolutionary algorithms; immune algorithms; interactions; knowledge storage; metaphor; swarm algorithms; Ant colony optimization; Artificial immune systems; Biological cells; Centralized control; Control systems; Evolutionary computation; Genetic algorithms; Gold; Neural networks; Particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN
981-04-7524-1
Type
conf
DOI
10.1109/ICONIP.2002.1203070
Filename
1203070
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