DocumentCode
2714623
Title
Modeling high-order human intelligence with intelligence of swarm
Author
Matsuka, Toshihiko ; Honda, Hidehito ; Kiyokawa, Sachiko ; Chouchourelou, Arieta
Author_Institution
Dept. of Cognitive & Inf. Sci., Chiba Univ., Chiba, Japan
fYear
2009
fDate
14-19 June 2009
Firstpage
2032
Lastpage
2037
Abstract
Particle swarm optimization (PSO) is a type of meta-heuristic optimization method built on the basis of the principle of collective behaviors exhibited by simple organisms. Although PSO is a model of social behaviors, the present research attempts to model learning behaviors of an individual human with PSO in order to evaluate our hypothesis that the dynamics of knowledge that are being acquired and updated in our mind resemble the dynamics of social interactions exhibited by swarms. A simulation study showed that a cognitive model with PSO was able to replicate not only manifested cognitive behaviors but also latent cognitive behaviors, resulting in the acquisition of at least two dissimilar yet functional solutions for a given task.
Keywords
cognitive systems; learning (artificial intelligence); particle swarm optimisation; cognitive model; high-order human intelligence; latent cognitive behaviors; learning behaviors; metaheuristic optimization method; particle swarm optimization; social behaviors; social interactions; Animals; Bayesian methods; Cognition; Humans; Information science; Intelligent networks; Optimization methods; Organisms; Particle swarm optimization; Psychology;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location
Atlanta, GA
ISSN
1098-7576
Print_ISBN
978-1-4244-3548-7
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2009.5179062
Filename
5179062
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