It seems that genes play a kind of ‘game’ during sexual recombination. Now, a distinguished Greek scientist who works in the USA has found an algorithm to describe this game.
Professor of computer science Christos Papadimitriou together with his colleagues of the University of California-Berkeley created an algorithm which explains sex from an evolutionary standpoint. It attempts to illustrate how sex makes it possible for genes to recombine into a new body, which in combination with natural selection in the environment creates a great diversity of life.
The role of sex in evolution has always been considered paradoxical by biologists because through sexual recombination, the offspring inherits only the half of parents’ “good” genes. Thus, it is difficult to explain how exactly natural selection results in desirable genetic variations.
The innovation in the approach proposed by Papadimitriou lies in the analysis of the evolution and sex from the perspective of computing and game theory. As the scientist said, “genes have a preference for a 50-50% rather than a 90-10% distribution. If we use an analogy with gambling, the genes want to hedge their bets. Even when there is a very successful genetic trait, evolution does not want to let the genes for other traits disappear, in case they are needed later.”
While every single random person can be either genetically successful or not, the overall genetic mixture of mankind improves over time. Using the terms of gaming, it is a “coordination game”, which is aimed at the wider good.
To describe the rules of this ‘game’ evolution plays through sexual recombination, the scientists found an algorithm, which has already been used in finance as a way of managing stock portfolios.
The key point of this method is to distribute the investment in many stocks, and to constantly adjust the holdings in each of them to monitor performance. If a stock is doing well, the investor raises the holdings correspondingly to how well it did, and vice versa.
As a result, such slow and patient adjustments lead to the nearly the same good performance as if you invested only in a few successful stocks. Returning to the main subject of this article, we can say that the role of sex in evolution works just like this investment method.
As Prof Papadimitriou said, this algorithm “is remarkably effective, and its use in computer science does wonders. As we are noticing now, nature uses this algorithm, which helps us understand why evolution has been so successful.”
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