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
Link To Document :
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