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
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;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2013 IEEE International Conference on
Conference_Location :
Manchester
DOI :
10.1109/SMC.2013.241