• DocumentCode
    539328
  • Title

    Toward crowd-sourcing social intelligent agents: Knowledge request-broker system and its implementation

  • Author

    Khandan, Hamed ; Terano, Takao

  • Author_Institution
    Dept. of Comput. Intell. & Syst. Sci., Tokyo Inst. of Technol., Yokohama, Japan
  • fYear
    2010
  • fDate
    Nov. 30 2010-Dec. 2 2010
  • Firstpage
    399
  • Lastpage
    403
  • Abstract
    A new approach to problem solving is introduced in this paper, featuring autonomous social agents, in which, simple agents with limited problem solving capabilities investigate a problem, digest small parts of it, and reunite in arbitrary social formations to represent the solution of the big problem as a whole. The social model is inspired by free formed business value-chain model, and agents behave on the basis of freedom and joy. The solution is implemented thanks to our knowledge request-broker architecture (KnoRBA), which facilitates better cooperation and mutual understanding between heterogeneous rational agents. Results show the successful construction of problem solving society by autonomous agents which efficiently solves a problem far beyond the capability of any single of them, which in turn confirms the usefulness of KnoRBA platform.
  • Keywords
    mobile agents; multi-agent systems; problem solving; social sciences computing; KnoRBA platform; autonomous social agents; crowd sourcing social intelligent agents; free formed business value-chain model; heterogeneous rational agents; knowledge request-broker architecture; problem solving; Biological system modeling; Computer architecture; Economics; Mixers; Problem-solving; Training; Training data; Artificial Social Intelligence; Crowd-sourcing; Ensemble Methods; Interest-Driven Behavior; Knowledge Request-Broker;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Information Management and Service (IMS), 2010 6th International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4244-8599-4
  • Electronic_ISBN
    978-89-88678-32-9
  • Type

    conf

  • Filename
    5713482