Biological immune system by evolutionary adaptive learning of neural networks

Author

Oeda, Shinichi ; Icmmura, T. ; Yamashita, Toshiyuki

Author_Institution

Graduate Sch. of Eng., Tokyo Metropolitan Inst. of Technol., Japan

Volume

2

fYear

2002

fDate

6/24/1905 12:00:00 AM

Firstpage

1976

Lastpage

1981

Abstract

Artificial immune systems have been identified as artificially intelligent systems. Some algorithms have been developed on this antigen-antibody response. Here, a model is presented wherein the behavior of each immune cell is specified. We improve this model using knowledge of the major histocompatibility complex. For this purpose an evolutionary neural network was used. Qualitative analysis of the results offers verification of the effectiveness of this approach to simulating an immune system

Keywords

artificial life; evolutionary computation; learning (artificial intelligence); neural nets; antigen-antibody response; artificially intelligent systems; biological immune system; evolutionary adaptive learning; evolutionary neural network; histocompatibility complex; immune cell; neural networks; qualitative analysis; Adaptive systems; Artificial immune systems; Artificial neural networks; Biological system modeling; Biology computing; Immune system; Neural networks; Pathogens; Protection; Weapons;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-7282-4

Type

conf

DOI

10.1109/CEC.2002.1004546

Filename

1004546