A genetic algorithm is an optimization heuristic that is inspired by the principles that drive natural evolution: mutation, recombination and selection. In comparison to traditional search methods such as hill-climbing, genetic algorithms have the ability to escape from local minima/maxima.
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Genetic algorithm for Clever Algorithms project
I wrote a bunch of Ruby code for a book project I've just finished. One criticism is that it is fine code but not very "ruby like". I agree my style was simplified for communication reasons, and ...
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Genetic algorithm for “Hello World”
This programme uses a genetic algorithm to get the string "Hello, World!". It can be summarized as follows:
Create a random initial population.
Let the best ...
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Genetic algorithm for “Hello World”
I've written an Erlang implementation of the genetic algorithm for a "Hello World" program as described here.
This is my first time writing any code in Erlang and also my first time writing code in a ...
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Where equations are born and mutants are buried
I've read up on genetic programming yesterday so I figured I'd try to implement something myself. I would like the main focus to be on whether or not I've implemented the idea behind it correctly.
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