So What are Genetic Algorithms?
Posted on January 12, 2009 Comments (1)
Genetic Algorithms: Cool Name and Damn Simple is a very nice explanation with python code of genetic algorithms.
What Can Genetic Algorithms Do?
In a word, genetic algorithms optimize. They can find better answers to a question, but not solve new questions. Given the definition of a car, they might create a better car, but they’ll never give you an airplane.
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For each generation we’ll take a portion of the best performing individuals as judged by our fitness function. These high-performers will be the parents of the next generation.
In a word, genetic algorithms optimize. They can find better answers to a question, but not solve new questions. Given the definition of a car, they might create a better car, but they’ll never give you an airplane.
…
For each generation we’ll take a portion of the best performing individuals as judged by our fitness function. These high-performers will be the parents of the next generation.
We’ll also randomly select some lesser performing individuals to be parents, because we want to promote genetic diversity. Abandoning the metaphor, one of the dangers of optimization algorithms is getting stuck at a local maximum and consequently being unable to find the real maximum. By including some individuals who are not performing as well, we decrease our likelihood of getting stuck.
Related: DNA Seen Through the Eyes of a Coder – Evolutionary Design – Algorithmic Self-Assembly – The Chip That Designs Itself
Posted by curiouscat
Categories: Research, Students
Tags: computer science, evolution, how things work, programming, science explained
Categories: Research, Students
Tags: computer science, evolution, how things work, programming, science explained
One Response to “So What are Genetic Algorithms?”
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April 26th, 2009 @ 9:19 am
“Evolution and learning (or phylogenetic and ontogenetic adaptation) are two forms of biological adaptation that differ in space and time. Evolution is a process of selective reproduction and substitution based on the existence of a population of individuals displaying variability at the genetic level. Learning, instead…”