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19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers)
A Model of Multi-Agent System Based on Immune Evolution
Taipei, Taiwan
March 25-March 30
ISBN: 0-7695-2249-1
ASCII Text
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Guangzhu Chen, Zhishu Li, Daohua Yuan, null Nimazhashi, "A Model of Multi-Agent System Based on Immune Evolution," 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), vol. 1, pp. 53-58, 19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers), 2005.
 
 
BibTex
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@article{ 10.1109/AINA.2005.36,
author = {Guangzhu Chen and Zhishu Li and Daohua Yuan and null Nimazhashi},
title = {A Model of Multi-Agent System Based on Immune Evolution},
journal ={2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA)},
volume = {1},
year = {2005},
issn = {1550-445X},
pages = {53-58},
doi = {http://doi.ieeecomputersociety.org/10.1109/AINA.2005.36},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA)
TI - A Model of Multi-Agent System Based on Immune Evolution
SN - 1550-445X
SP53
EP58
A1 - Guangzhu Chen,
A1 - Zhishu Li,
A1 - Daohua Yuan,
A1 - null Nimazhashi,
PY - 2005
KW - null
VL - 1
JA - 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA)
ER -
 
Guangzhu Chen, Sichuan University and China University of Mining and Technology
Zhishu Li, Sichuan University
Daohua Yuan, Sichuan University
null Nimazhashi, Sichuan University
Increasingly, multi-agent systems are being designed for a variety of complex, dynamic and uncertain domains. An agent in such domains often needs to learn or evolve to adjust its behaviors, or negotiate with other agents, and so on. Immune cells are the key components of the human immune system, their evolutions in the whole lifecycle directly decide the immune system?s performance. In this paper, a model of immune evolution multi-agent system (IEMAS) is introduced based on immune cells? evolution principles. In such a system agents can evolve to adapt to the complex, dynamic and uncertain environment. Also, the formal model of IEMAS is described, and then the mature immune cell evolution algorithm and the memory immune cell evolution algorithm of IEMAS are presented. Finally, the run of IEMAS applied to the task allocation in multi-agent systems are presented and displays the efficiency of IEMAS in the complex, dynamic and uncertain environment.
Citation:
Guangzhu Chen, Zhishu Li, Daohua Yuan, null Nimazhashi, "A Model of Multi-Agent System Based on Immune Evolution," aina, vol. 1, pp.53-58, 19th International Conference on Advanced Information Networking and Applications (AINA'05) Volume 1 (AINA papers), 2005
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