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Rule based Emotion Recognition using Ant Colony Optimization

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Emotion-Recognition

Rule based Emotion Recognition using Ant Miner.
Ant Colony Optimization falls under the category of swarm intelligence algorithms, commonly used as a metaheuristic. It is, unsurprisingly, inspired from ants. The problem is formulated as a traversible field in which numerous ants are deployed. They follow a path dictated by the phermone levels and a problem-specific heuristic, in a probabilistic way. In this setting, the ants’ paths are possible solutions and depending upon the quality, pheromones are updated in the field for the next batch of ants to consider. After sufficient iterations, the best solutions are taken.
Check out the project page on my website for pretty much the same text, and a link back to here!

Group Members:

Amogh Bharadwaj [2019A7PS0086H]
Subienay Ganesh Ratnam [2019A7PS0096H]
Pranav Balaji [2019A7PS0040H]

Code organisation:

In the master branch, the vanilla implementation of Ant Miner is present.
In the c-Ant Miner branch, the implementation for c-Ant Miner is present.

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Rule based Emotion Recognition using Ant Colony Optimization

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