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copied!<p>You can anneal the mutation rate over time to get the sort of convergence behavior you're describing. But I actually think there are probably bigger gains to be had by modifying other parts of your algorithm.</p> <p>Roulette wheel selection applies a very high degree of selection pressure in general. It tends to cause a pretty rapid loss of diversity fairly early in the process. Binary tournament selection is usually a better place to start experimenting. It's a more gradual form of pressure, and just as importantly, it's much better controlled.</p> <p>With a less aggressive selection mechanism, you can afford to produce more offspring, since you don't have to worry about producing so many near-copies of the best one or two individuals. Rather than 12% of the population producing offspring (possible less because of repetition of parents in the mating pool), I'd go with 100%. You don't necessarily need to literally make sure every parent participates, but just generate the same number of offspring as you have parents.</p> <p>Some form of mild elitism will probably then be helpful so that you don't lose good parents. Maybe keep the best 2-5 individuals from the parent population if they're better than the worst 2-5 offspring.</p> <p>With elitism, you can use a bit higher mutation rate. All three of your operators seem useful. (Note that #3 is actually a form of local search embedded in your genetic algorithm. That's often a <em>huge</em> win in terms of performance. You could in fact extend #3 into a much more sophisticated method that looped until it couldn't figure out how to make any further improvements.)</p> <p>I don't see an obvious better/worse set of weights for your three mutation operators. I think at that point, you're firmly within the realm of experimental parameter tuning. Another idea is to inject a bit of knowledge into the process and, for example, say that early on in the process, you choose between them randomly. Later, as the algorithm is converging, favor the mutation operators that you think are more likely to help finish "almost-solved" boards.</p>

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