Particle swarm optimization is a problem solving technique for solving problems where the answer can be represented as a point in n-dimensional space. Hypotheses are plotted in this space and given a velocity and direction, as well as a communication channel between the particles. Particles then "move" through the solution space, and are evaluated for fitness at each iteration. Particles adjust their velocity and direction towards those particles within its communication grouping which have better fitness values.
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