in reply to Evolving formulae

The program at hand pretty much does that: Mutate all formulas, find the best and reward them. With some twists and turns.
This is all well known. It's also well known that "just finding the best" isn't always the best approach. It's an approach that will only work if in the field of all possible approximations, there's always a monotone path (that is, every next approximation is better) towards the ultimate goal. However, if that's the case, there's usual an efficient, direct way of solving the problem.

The interesting problems are when there aren't always monotone paths towards the end goal; that is, there are local maxima, and you may have to first decrease your current approximation to be able to further increase it.

Unfortunally, your description isn't clear whether your technique does such a thing.

Abigail

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Re: Re: Evolving formulae
by tsee (Curate) on Feb 25, 2004 at 15:16 UTC

    Admittedly, the node doesn't completely describe the program.

    In the example case of evolving formulae of constants and operators only, most mutations are pretty significant. Thus, most changes except number increment/decrement should have a strong effect on the result.

    Since most immediate changes to the existing structure yield worse results, you can customize the number of generations to evolve before the "fittest" cells spread to their neighbours.

    An interesting varation might be to introduce some kind of mixture of two cells whenever one overwrites another.

    Steffen

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