Title :
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
fDate :
6/24/1905 12:00:00 AM
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;
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1004546
