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Why? We do long-term experiments in biology because genetic evolution is slow - whereas with genetic programming we can speed it up limited only by the computin
by JimmyL 17y ago
Why? We do long-term experiments in biology because genetic evolution is slow - whereas with genetic programming we can speed it up limited only by the computing technology.
Let's say biological evolution has been going for 4.5 Billion years, at an average of one mutation per second for all that time. A quick search says that a modern Core 2 Extreme can process about 50,000 MIPS. Let's say that each mutation takes 100 instructions on average (including set-up and tear-down, etc.), and that we have 5,000 MIPS available for this calculation process - then it would be possible to do all that calculation in about 9 seconds of CPU time.
Bottom line - even if my back-of-the-envelope calculation about is two or three orders of magnitude off - is that you don't need you run a long-term experiment to give genetic algorithms the same amount of run-time as nature had with us, you just need a few bucks of AWS credit.
- yannis 17y ago>Bottom line - even if my back-of-the-envelope calculation about is two or three orders of magnitude off - is that you don't need you run a long-term experiment to give genetic algorithms the same amount of run-time as nature had with us, you just need a few bucks of AWS credit Depends on the simulation, anything approaching an accurate simulation C A N N O T currently be simulated with the technology we have. Take for example the evolution of the brain. A human brain consists of 100 billion nerve cells. A supercomputer simulating an organ this complicated -- using current technology -- would take up the space of several soccer fields and draw $3 billion worth of electricity every year. http://www.spiegel.de/fotostrecke/fotostrecke-19430.html http://www.spiegel.de/fotostrecke/fotostrecke-19430.html Similar orders of magnitude are applicable to the genome of a fruitfly or an amoeba. There is no satisfactory simulation of a cell ....
- JimmyL 17y agoTrue - but I don't think that's what the author is talking about. You can't simulate biological world-scale evolution right now. As you say, it's just too complex and operating at too large a scale. We somewhat know how, but the technology to actually do it isn't there yet. Genetic programming, on the other hand, we can do. It's generally used as part of an optimization process, and is simple enough that we can simulate it quite well. To give those processes the amount of run-time that resulted in us (which is what I interpreted the author as talking about) would be trivial, as I showed. To create a virtual world, start it up with some amino acids and a jolt of lightning, and end up with us is way beyond our capability right now - and probably wouldn't end up with "us" anyways, owing to the randomness in there.
- yannis 17y agoYou correct about the usefulness of GP in CS, I am not so sure of its usefulness in Biology (since we define the fitness factors rather than nature and an uncontrolled environment). My favorite application from the Hummies Awards, self-correcting programs http://www.genetic-programming.org/hc2009/1-Forrest/Forrest-Text-File.txt http://www.genetic-programming.org/hc2009/1-Forrest/Forrest-...
- kbob 17y agoFurthermore, biological evolution experiments with immense population sizes in parallel. At the low extreme, there are about 10 to the 10th humans in the current generation. At the high extreme, there are (very approximately) 10 to the 20th algae in the current generation. So you'll need somewhere north of 10 to the 10th of those soccer field sized mainframes.