# Artificial Intelligence #8 : Particle Swarm Optimization

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Link : Artificial Intelligence #8 : Particle Swarm Optimization
Particle swarm optimization (PSO) is an artificial intelligence (AI) technique that can be used to find approximate solutions to extremely difficult or impossible numeric maximization and minimization problems. ... PSO is loosely modeled on group behavior, such as bird flocking and fish schooling.by Sobhan N

What you'll learn

• You'll know the ideas behind Particle Swarm Optimization Method.
• You'll learn how to write programs with python and deap library to solve Min/Max problem.
• You'll learn how particles work to find the optimum point of the function
• You'll learn how cognitive and social coefficients are work.
• You'll know how to optimize simple functions.
• You'll know how to find optimum point for complicated Trigonometric functions.
• You'll learn how to solve well known standard functions like Rastrign.

Description
Do you like to know  the basic theory behind Particle Swarm  Optimization Method?

Do you like to learn how to solve optimization problems like Min/Max finding  with Particle Swarm Optimization Method?

Do you like to know how to find minimum of Rastrigin standard optimization function with a few lines of codes an Particle Swarm?

If you say Yes so read more ...

In computational science, Particle Swarm Optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. It solves a problem by having a population of candidate solutions, or particles, and moving these particles around in the search-space according to simple mathematical formula over the particle's position and velocity.

In this course I want to learn you theory behind Particle Swarm Optimization Method. You'll learn basic concepts of Particle Swarm and how they are work.

Then we go further you will learn how to use python and deap library to solve optimization problem and find Min/Max points for your desired functions.
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