Since human intelligence presumably is a function of a natural genetic algorithm in nature, is using a genetic algorithm in a computer an example of artificial intelligence? If not, how do they differ? Or perhaps some are and some are not expressing artificial intelligence depending upon the scale of the algorithm and what it evolves into?
- An ability that is commonly attributed to intelligence is problem solving.
- Another one is learning (improving itself from experience).
- Artificial intelligence can be defined as "replicating intelligence, or parts of it, at least in appearance, inside a computer" (dodging the definition of intelligence itself).
- Genetic algorithms are computational problem solving tools that find and improve solutions (they learn).
Thus, genetic algorithms are a kind of artificial intelligence.
Regarding scale, I don't see it as an important factor for defining G.A. as A.I or not. The same way we can simply classify different living forms as more or less intelligent instead of just saying intelligent or not intelligent.
Finally, let's just make an important distinction: our brains are the product of natural selection, but the brains themselves don't use the same principle in order to achieve intelligence.
This is probably more a question of philosophy than anything. In terms of how things are commonly defined, I'll say "yes, genetic algorithms are part of AI". If you pick up a comprehensive book on artificial intelligence, there will probably be a chapter on genetic algorithms (or more broadly, evolutionary algorithms).
One area that has been extensively studied in the past is the idea of using genetic algorithms to train neural networks. I don't know if people are still actively researching this topic or not, but it at least illustrates that GA's are part of the overall rubric of AI in one regard.
The notion of genetics used in Genetic Algorithms (GAs) is a very stripped down version relative to genetics in nature, essentially consisting of a population of 'genes' (representing solutions to some predefined problem) subject to `survival of the fittest' during iterated application of recombination and mutation.
Nowadays, the term 'Computational Intelligence' (CI) tends to be used to describe computational techniques intended to produce `the appearance of intelligence by any computational means', rather than specifically attempting to mimic the mechanisms that are believed to give rise to human (or animal) intelligence.
That said, the distinction between CI and AI is not so hard and fast, and arguably arose during the `AI Winter' when the term AI was out of fashion.
Human intelligence is not an example of natural genetic algorithms.
Genetic algorithms have collections of solutions that are collided with each other to make new solutions, eventually returning the best solution. Human intelligence is a network of neurons doing information processing, and almost all of it doesn't behave the same way.
But that something doesn't behave in the same way that human intelligence does doesn't mean that it's not an AI algorithm; I would include 'genetic algorithms' as a numerical optimization technique, and since optimization and intelligence are deeply linked any numerical optimization technique could be seen as an AI technique.
To answer this question, you must first know what is intelligence, and since there is no clear line between intelligent and not, this question is more philosophical rather than technical.
In my opinion, intelligence is the ability to define a problem and find a way to solve it using memory and reasoning. Since a genetic algorithm follows this structure, I would say that it falls under the category of artificial intelligence.