DocumentCode
3498286
Title
Immune, swarm, and evolutionary algorithms. Part I: basic models
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
1464
Abstract
These two papers have three main aims. First (Part I), to review the general algorithms of immune, swarm and evolutionary systems. Second (Part II), to present a philosophical discussion about the similarities and differences between these paradigms, in terms of components, architecture, adaptation, interactions, and metaphors. Finally (Part II), to highlight the main features embodied in each approach, such that avenues for the creation of hybrid models can be suggested.
Keywords
artificial intelligence; genetic algorithms; multi-agent systems; ant colony optimization; artificial immune systems; evolutionary algorithm; evolutionary systems; particle swarm optimization; Biological cells; Biological system modeling; Evolution (biology); Evolutionary computation; Genetic algorithms; Genetic mutations; Genetic programming; Immune system; Intelligent agent; Intelligent robots;
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.2002.1203069
Filename
1203069
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