Immunity clonal strategies

Author

Ruochen, Liu ; Haifeng, Du ; Licheng, Jiao

Author_Institution

Natinal Key Lab. for Radar Signal Process., Xidian Univ., Xi´´an, China

fYear

2003

fDate

27-30 Sept. 2003

Firstpage

290

Lastpage

295

Abstract

Based on the clonal selection theory, the main mechanisms of clone, which will be explored in the field of artificial intelligence, are analyzed in this paper. An improved evolutionary strategy algorithm, immunity clonal strategy algorithm (ICS), which includes immunity monoclonal strategy algorithm (IMSA) and immunity polyclonal strategy algorithm (IPSA), is put forward. Compared with the classical evolutionary strategy algorithm (CES), ICS is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like multi-objective optimization, and the results are better. Using the theories of Markov chain, it is proved that ICS algorithm is convergent.

Keywords

Markov processes; artificial life; evolutionary computation; learning (artificial intelligence); Markov chain; artificial intelligence; classical evolutionary strategy algorithm; clonal selection theory; clone; complex machine learning task; immunity clonal strategy algorithm; immunity monocolonal strategy algorithm; immunity polyclonal strategy algorithm; multiobjective optimization; Artificial intelligence; Cloning; Computational modeling; Computer simulation; Evolution (biology); Genetic mutations; 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.2003.1238140

Filename

1238140