priya-sb / cohort-intelligence

Implementation of Cohort Intelligence algorithm in Python

Cohort-Intelligence

This project includes the python implementation of an optimization technique referred to as Cohort Intelligence (CI) developed by Dr. Anand J Kulkarni in 2013. CI is based on artificial intelligence (AI) concepts. It attempts to model the behavior often observed in a self-organizing system in which candidates in a cohort interact and compete with one another in order to achieve shared goals. Each candidate tries to improve its own behavior by observing the behavior of every other candidate in that cohort. Each candidate in the cohort follows a certain behavior which may result in the improvement of its own behavior. When a candidate attempts to follow a given behavior characterized by certain qualities, it often adopts such qualities in a manner that may improve its own goal. In this way, candidates in the cohort learn from one another which, in time, helps improve the behavior of the entire group. The cohort’s behavior as a whole is said to have reached saturation (convergence) if, over a considerable number of learning attempts, the individual behavior of all candidates does not improve considerably making it difficult to distinguish between them. In other words, the difference between the individual behaviors of the candidates becomes insignificant.

The mathematical working of the CI algorithm has been explained in the CI Illustation pdf document attached.

Results:

Convergence

Range of variable x0 for Candidate0

Range of variable x1 for Candidate0

Range of variable x0 for Candidate1

Range of variable x1 for Candidate1

Range of variable x0 for Candidate2

Range of variable x1 for Candidate2