• DocumentCode
    677886
  • Title

    Cohort Intelligence: A Self Supervised Learning Behavior

  • Author

    Kulkarni, Anand J. ; Durugkar, Ishan P. ; Kumar, Manoj

  • Author_Institution
    Optimization & Agent Technol. (OAT) Res. Lab., Maharashtra Inst. of Technol., Pune, India
  • fYear
    2013
  • fDate
    13-16 Oct. 2013
  • Firstpage
    1396
  • Lastpage
    1400
  • Abstract
    By virtue of the collective and interdependent behavior of its candidates, a swarm organizes itself to achieve a particular task. Similarly, inspired from the natural and social tendency of learning from one another, a novel concept of Cohort Intelligence (CI) is presented. The learning refers to a cohort candidate´s effort to self supervise its behavior and further adapt to the behavior of other candidate which it intends to follow. This makes every candidate to improve/evolve its own and eventually the entire cohort behavior. The approach is validated by solving four test problems. The advantages and limitations are also discussed.
  • Keywords
    learning (artificial intelligence); optimisation; cohort behavior; cohort intelligence; self supervised learning behavior; Conferences; Convergence; Genetic algorithms; Optimization; Particle swarm optimization; Silicon; Supervised learning; Cohort Intelligence; Nature-inspired Optimization; Self Supervised Learning;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
  • Conference_Location
    Manchester
  • Type

    conf

  • DOI
    10.1109/SMC.2013.241
  • Filename
    6721994