Re:Evolutionary Algorithm: Evolving "Hello, World"
by bermanoid on Thursday September 29, 2011 @02:58PM
(#3053760)
There was too much randomness in his evolving. When I was evolving agents for my M.S., I used tournament selection (http://en.wikipedia.org/wiki/Tournament_selection) with an 80% crossover rate for the top 2 winners and only a 5% mutation rate on the offspring. I also started off with a population of 500 individuals. This approach seemed to produce much better results.
I don't know about that - with a population size of 500, every generation is very expensive to test, so your runway is a lot shorter.
I set up a test using your parameters, and it seemed to take an average of about 50 generations to evolve "Hello, World". That's a total of 50x500=25000 fitness evaluations (assuming you've cached results properly) to solve the problem. Whereas with a population size of 20, 100% crossover and mutation rates, the average is about 150 gens, for 150x20 = 3000 evaluations, beating your parameter set by a factor of 8.
Which doesn't mean much, other than that this is not such a good problem to use evolutionary methods on.
There was too much randomness in his evolving. When I was evolving agents for my M.S., I used tournament selection (http://en.wikipedia.org/wiki/Tournament_selection) with an 80% crossover rate for the top 2 winners and only a 5% mutation rate on the offspring. I also started off with a population of 500 individuals. This approach seemed to produce much better results.