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Biology is used in AI terminology. What are the reasons? What does biology have to do with AI? For instance, why is the genetic algorithm used in AI? Does it fully belong to biology?

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  • $\begingroup$ It's important to know, that every subject outside of AI has to do with AI. Not only biology can be explained with machine learning and expert systems but the same is possible for chemistry, architecture and even macro-economics. AI can be imagined as a meta-science which is on top of any other science. Or to explain it from the opposite side: if somebody isn't familiar with Artificial Intelligence he won't understand biology. $\endgroup$ – Manuel Rodriguez Dec 9 '18 at 6:17
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Biological life is the only form of intelligence life that we are aware of. Biology is often an inspiration to AI researchers to develop artificial intelligence.

There are numerous examples of AI models and algorithms that have been introduced (at least, partially) based on or inspired by the biology. For example, reinforcement learning is based on the way (certain) animals learn. Artificial neural networks are very approximative models of human neural networks. All the genetic algorithms are roughly based on Darwin's theory of evolution. Ant colony optimization algorithms (and, in general, swarm intelligence) are based on the way real ants behave.

I had once read that there are cases where AI discoveries have also helped the development of the biology field.

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  • $\begingroup$ What is 'biological life'? $\endgroup$ – DuttaA Mar 22 at 16:54
  • $\begingroup$ @DuttaA Humans, ants, bees, dogs and plants are all examples of biological living beings. $\endgroup$ – nbro Mar 22 at 16:58
  • $\begingroup$ For example, I think that a chess engine that plays chess at a superhuman level cannot be considered intelligent. It only knows how to play chess, and that's it. It would die or lose in any other circumstance (without the intervention of a human). I would say the same thing about AlphaGo and similar systems. $\endgroup$ – nbro Mar 22 at 18:00
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I see the connection arising mostly thought Evolutionary Game Theory and Evolutionary Algorithms. Evolutionary algorithms are an analog of natural selection, where successive generations of a given decision making agent are more optimized than previous generations. Like organisms in nature, this process uses "reproduction, mutation, recombination and selection".

There are a couple of recent articles from Quanta Magazine. One, "The Math That Tells Cells What They Are" discusses mathematical optimization as the core function of fundamental biological systems.

“Through evolution, these cells have figured out how to implement Bayes’ trick using regulatory DNA.”

"“Natural selection [seems to be] pushing the system hard enough so that it … reaches a point where the cells are performing at the limit of what physics allows.”

This second quote is exactly the goal of Artificial Intelligence, where utility is limited by physics (computing resources). One way for an algorithm to increase utility is to increase computing power, but the other method is to refine the algorithm to make strong decisions more efficiently. (MCTS vs. Brute Force where a model is intractable, as an example.)

A second article "Mathematical Simplicity May Drive Evolution’s Speed" talks about Genetic Algorithms

"Creationists love to insist that evolution had to assemble upward of 300 amino acids in the right order to create just one medium-size human protein. With 20 possible amino acids to occupy each of those positions, there would seemingly have been more than 20300 possibilities to sift through, a quantity that renders the number of atoms in the observable universe inconsequential."

The game of Go on a 19x19 board has a similar quality--the number of potential gamestates is vastly exceeds the number of atoms in the universe, and, even if the entire universe were converted to computronium, the game would still be intractable.

"The fatal flaw in their argument is that evolution didn’t just test sequences randomly: The process of natural selection winnowed the field. Moreover, it seems likely that nature somehow also found other shortcuts, ways to narrow down the vast space of possibilities to smaller, explorable subsets more likely to yield useful solutions."

This would also be an accurate description the process of pruning a search space. The article concludes that, although there is still much research to be conducted:

“The idea of thinking about life as evolving software is fertile.”

The process of optimization in nature and in computer science is similar in spirit, if not in fact.

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The second factor may arise out of the mythology of AI, via speculative fiction. In science fiction, the idea of automata as a form of artificial life is persistent. Shows & films like Westworld, BladeRunner, and the Alien franchise, with David the Android as a prime example of a superior, artificial species that may supplant humanity, are extremely popular. These are all based on Phillip K Dick's ideas explicated in Do Androids Dream of Electric Sheep, the plot of which turns on evolutionary game theory, written about 5 years before the field was formalized! (Dick's influence can even be seen in Google's "Nexus" naming convention for their Android phone;) Underneath all of this is also the idea that Artificial Intelligence itself is a function of nature, with humans as merely the vehicle for the next form of dominant life.

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