Swarm Intelligence: The Nature-Inspired Artificial Intelligence Which Uses both

Posted by Sachin CMI on December 14th, 2020

The idea of Swarm Intelligence is not very far from the traditional idea of crowds. Crowds are basically groups of people or animals who work together to achieve a common goal. In the case of swarms, humans take the form of the swarms while the animals become the resources or the brains of the swarm. As in the case of the human swarm, the collective intelligence is used to accomplish the collective goal.

Swarm intelligence is all about applying the collective intelligence of a group of computers to solve a problem in a self-organized manner. Basically, it is an integrated range of computer science method, which uses both supervised and unsupervised learning. As with the traditional concept of supervised learning, the logic of the application is fed into the algorithm through a supervised memory. The logic is fed into the algorithm is typically either a supervised backtesting or an unsupervised backtesting. Therefore, swarm intelligence refers to both supervised and unsupervised learning.

Traditional logic networks such as Backpropagation and the neural network models are the backbone of swarm intelligence. In the context of the latter, the logic is fed into the simulation rather than directly into the real software.       

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