DocumentCode
2861780
Title
An Analytical Approach to the Similarities between Swarm Intelligence and Artificial Immune System
Author
Xiao, Renbin ; Chen, Tinggui ; Tao, Zhenwu
Author_Institution
Inst. of Syst. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear
2011
fDate
16-18 Dec. 2011
Firstpage
112
Lastpage
115
Abstract
Swarm intelligence and artificial immune system (AIS) are both derived from imitation of nature biology system. Their common characteristic is that they both have simple individuals but appear emergence characteristic in population level through interaction among individuals. In order to explore inherent similarity of complex system, we take ant colony system (ACS) and AIS as objectives to study this similarity in this paper. From the similarity of system structure, we firstly analyze the similarities of artificial ants and artificial immune cells from individual structure, action and relationships among individuals, and then the similarity of system network structure based on interaction between individuals is discussed. Finally, the similarity of their operation environment is also compared. From the similarity of system operation mechanism, we firstly investigate the difference of ACS and AIS in individual and population level. After that, the effects of memory mechanism of these two algorithms on operation are also studied. At last, we further point out the similarity of diversity strategies. The purpose of the above work is to construct the inherent relationship among different bio-inspired computation methods, which has both important theoretic significance and practical value to reveal the generation and operation mechanisms of human intelligence.
Keywords
ant colony optimisation; artificial immune systems; ACS; AIS; ant colony system; artificial ants; artificial immune cells; artificial immune system; bio-inspired computation methods; diversity strategy; human intelligence; swarm intelligence; system operation mechanism; Algorithm design and analysis; Educational institutions; Immune system; Learning; Libraries; Negative feedback; Particle swarm optimization; artificial immune system; bionicis; complex system; similarity; swarm intelligence;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovations in Bio-inspired Computing and Applications (IBICA), 2011 Second International Conference on
Conference_Location
Shenzhan
Print_ISBN
978-1-4577-1219-7
Type
conf
DOI
10.1109/IBICA.2011.32
Filename
6118682
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