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Genetic Algorithms Explained : A Python Implementation

Written by @luizguilhermefr | Published on 2020/2/14

TL;DR
Genetic Algorithms Explained : A Python Implementation : a Python Implementation. The problem we will try to solve here is to find the maximum of a 3D function similar to a hat. It is based on three concepts: selection, reproduction, and mutation. We generate a random set of individuals, select the best ones, cross them over and mutate the result. We will iterate over several generations improving it until we find an acceptable solution. To select individuals to reproduce, we use a widely adopted method called roulette wheel.

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Written by
@luizguilhermefr
Computer Scientist, Software Engineer @ Loadsmart, Machine Learning enthusiast

Topics and
tags
algorithms|genetic-algorithms|python|hackernoon-top-story|natural-selection-theory|charles-darwin|david-e-goldberg|programming
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