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>Introduction >Background and Method >Demo >Application >Comparison with GA >Artificial Intelligence > References

 

Introduction

Swarm Intelligence is kind of computation , inspired by the swarm behaviour of flocks of bird and schools of fish . In 1995 , Dr. Eberhart and Dr. Kennedy showed an optimization technique , based on the principles of swarm intelligence . This is generally known as Particle Swarm Optimization , and is of immense use in solving continuous optimization problems , even though the idea can also be used for discrete optimization problems as well .

Very often , natural creatures like birds and fish , behave in a swarm . For instance , consider a flock of bird , where each bird has a limited vision . There is some food lying around . Even though a bird may not know exactly where the food is , by observing the birds in its flock , it will go towards the bird closest to the food , and by doing so a number of times it ultimately reaches its goal ( food ) . Particle Swarm Optimization ( PSO ) is an optimization technique , based on the principles of swarm intelligence . Swarm intelligence , is generally associated with groups of autonomous or asynchronous agents .

PSO has found a variety of applications : optimization , artificial intelligence and control .

 

>Introduction >Background and Method >Demo >Application >Comparison with GA >Artificial Intelligence > References