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{{Short description|Family of stochastic optimization methods}}
[[Image:Eda mono-variant gauss iterations.svg|thumb|350px|Estimation of distribution algorithm. For each iteration ''i'', a random draw is performed for a population ''P'' in a distribution ''PDu''. The distribution parameters ''PDe'' are then estimated using the selected points ''PS''. The illustrated example optimizes a continuous objective function ''f(X)'' with a unique optimum ''O''. The sampling (following a normal distribution ''N'') concentrates around the optimum as one goes along unwinding algorithm.]]
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