Modeling high-order human intelligence with intelligence of swarm

Authors:
Toshihiko Matsuka;Hidehito Honda;Sachiko Kiyokawa;Arieta Chouchourelou
Affiliations:
Department of Cognitive and Information Science, Chiba University, Chiba, Japan;Department of Cognitive and Information Science, Chiba University, Chiba, Japan;Department of Psychology, Chubu University, Kasugai, Japan;School of Humanities and Social Sciences, European University Cyprus, Nicosia, Cyprus
Venue:
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Year:
2009

Citing 4
Cited 0

Swarm intelligence

Swarm intelligence
Fundamentals of Computational Swarm Intelligence

Fundamentals of Computational Swarm Intelligence
2008 Special Issue: Modeling a flexible representation machinery of human concept learning

Neural Networks
Toward a descriptive cognitive model of human learning

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

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.