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
Link To Document :
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