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I am trying to understand the difference between the workings biological evolution and artificial evolution. If we look at it in terms of genetics, in both of them, selection is the key term, natural selection in biological way and selection as in genetic algorithms than what's the difference in between artificial and biological evolution?

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  • $\begingroup$ Great question...here is a relevant link ai.stackexchange.com/questions/3009/… $\endgroup$ – DuttaA Mar 14 '18 at 13:38
  • $\begingroup$ @DuttaA , thanks for the link but it's a little different from what I asked, the question which is given in that link is related to the diffrence in between two algorithms, both of them are related to tech not with Biology, and here I asked the difference in between natural and artificial. $\endgroup$ – Germa Vinsmoke Mar 14 '18 at 13:50
  • $\begingroup$ I suppose artificial evolution doesn't necessarily model only biological evolution. It may contain techniques which are based on biological evolution, but it may not be restricted to the latter. $\endgroup$ – nbro Mar 14 '18 at 18:11
  • $\begingroup$ Biological evolution is determined by factors in finite construction and its limitations in genetic structure confined to those limits abstract evolution although a product of biological evolution has endless limits and is confined to produce reality constructed by evolutionary imagination with no boundaries and by our perception of the infinite we similarly all have. $\endgroup$ – Bobs Mar 18 '18 at 2:17
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Biological and artificial evolution work around pretty much the same principles.

Fitness and selection: In biology, the fittest organisms in an ecosystem are more likely to survive long enough to reproduce, passing on their genes in the process. In artificial evolution, our organisms are in fact solutions to our problem, which can be evaluated to determine how good they are (their fitness). We choose ourselves which solutions will be selected for reproduction (there are many ways to do this selection, but what is common among all of them is that the fittest solutions have a higher chance of being selected).

Crossover: In biology, an organism inherits a portion of each parent's genes, so is a sort of genetic hybrid of both parents. For artificial evolution, a new solution (a "child" solution) will inherit part of its parent's solutions (we take a partial solution from each parent, and glue those partial solutions together to construct a new solution).

Mutation: In nature mutations often occur at birth and this is why there are many different species. Harmful mutations make the individual less likely to survive long enough to pass them on to children, and in contrast helpful mutations make it more likely that the individual will survive long enough to pass them unto children. The same can be said for artificial evolution: A mutation randomly changes a small part of the solution, and if it makes that solution fitter, then that solution has a higher chance of being selected for reproduction.

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  • $\begingroup$ If we consider artificial selection or "selective breeding" then it'll fall in which part of the evolution? $\endgroup$ – Germa Vinsmoke Mar 14 '18 at 13:59
  • $\begingroup$ @GermaVinsmoke I'm not very familiar with the fields of biology and natural history, but I would say that "artificial selection" falls under a general biological/natural definition of "fitness" (e.g., a strong deer fighting a weak deer for mating rights with a female is more likely than his opponent to win the fight and breed, as he is "fitter"). $\endgroup$ – Philippe Olivier Mar 14 '18 at 15:17
  • $\begingroup$ Great answer...I think you missed one point about death..In bio evolution we can't go back to the original but in computer we can go back to previous versions...Am I correct? $\endgroup$ – DuttaA Mar 15 '18 at 12:36
  • $\begingroup$ @DuttaA Quite the contrary in my opinion. In biological evolution an organism could in theory transform back to something close to a previous form, if the selection pressure pushed it that way (a changing ecosystem means a changing definition of "fitness"). In contrast, with artificial evolution we are solving a specific problem so the "ecosystem" (the problem) is static, as is its objective. This means that since our solutions are getting fitter and fitter in relation to this static objective, it is unlikely that our method will drive us towards past solutions which we have already explored. $\endgroup$ – Philippe Olivier Mar 15 '18 at 16:19
  • $\begingroup$ @PhilippeOlivier I really don't think that happens, since in genetics they are always looking for a better form, we can't go back to chimpanzees however we try, since chimpanzee is not the best form, like entropy always increases and by carnot cycle you can never reach the initial form, I think the same goes for bio evolution...though I maybe wrong $\endgroup$ – DuttaA Mar 15 '18 at 16:37
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Selecting the fittest species is only what the audience sees from the evolution, in reality it works different. Suppose our aim is to implement a realtime strategy game with a civilization who is exploring a tech-tree. For the player it looks like the species improves himself and overcomes technology from the past. But in reality, the techtree was available since the beginning and it was only hidden from the player. That means, the game unhides in later iterations new features to create the illusion of evolution. It is not possible to create out of nothing something. Mutation or selection are only marketing description for Memetics (something which was already there). They are not explaining how the system works under the hood. Even games who are dedicated to natural selection like “Spore” (2008 videogame from Maxis) are nothing else than a 1 GB iso file, in which all the characters and maps are implemented and if the user reaches a certain goal, the species in the game were unlocked and made visible.

If this concept is also true for biological evolution (© by Charles Darwin) is unclear. In fact, for computergames evolution never works. Only the marketing description in Spore is based on survival of the fittest, the inner working of the game is devoted to something else.

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  • $\begingroup$ Great answer...Explores a different part of the question... Evolution also has finite number of outcomes but trees have even lesser number of outcomes $\endgroup$ – DuttaA Mar 15 '18 at 12:32

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