• 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