Adaptive polyclonal programming algorithm with applications

Author

Haifeng, Du ; Licheng, Jiao ; Ruochen, Liu

Author_Institution

National Key Lab. for Rader Signal Process., Xidian Univ., Xi´´an, China

fYear

2003

fDate

27-30 Sept. 2003

Firstpage

350

Lastpage

355

Abstract

Based on the clonal selection theory, the main mechanism of immune clone applied in artificial intelligence is analyzed in this paper. A new operator, adaptive polyclonal operator as well as a novel artificial immune system algorithm, APPA (adaptive polyclonal programming algorithm), is put forward. Compared with some other evolutionary programming algorithms (like breeder genetic algorithm), APPA, behaving as an evolutionary strategy, is shown to be capable of solving complex machine learning tasks effectively, like multimodal function optimization.

Keywords

adaptive systems; artificial life; evolutionary computation; learning (artificial intelligence); APPA; adaptive polyclonal operator; adaptive polyclonal programming algorithm; artificial immune system algorithm; artificial intelligence; breeder genetic algorithm; clonal selection; complex machine learning; evolutionary programming algorithm; immune clone; multimodal function optimization; Adaptive systems; Artificial immune systems; Artificial intelligence; Cloning; Functional programming; Genetic programming; Immune system; Machine learning; Machine learning algorithms; Signal analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Multimedia Applications, 2003. ICCIMA 2003. Proceedings. Fifth International Conference on

Print_ISBN

0-7695-1957-1

Type

conf

DOI

10.1109/ICCIMA.2003.1238150

Filename

1238150