From: Martin Ling (martin@nodezero.org.uk)
Date: Tue May 23 2000 - 02:23:24 MDT
On Tue, May 23, 2000 at 12:19:15AM -0400, Dan Fabulich wrote:
> Matt Gingel noted briefly:
>
> > In the general case, evolution is a graph search. Each possible
> > individual is a node, and mutations spell out the transition rules. By
> > manipulating the space of transition rules, we transform the search
> > space - we make some points closer together and some further
> > apart. Perhaps more importantly, local maxima can be eradicated
> > since we change the set reachable nodes. (This analysis still
> > holds if we consider crossover operators, every node becoming a
> > population.)
>
> Here's a good example of how someone might use GAs: they might be
> interested in finding out what the most aerodynamic design for a
> vehicle is. So they'd design a multi-dimensional space allowing for a
> variety of different things to be changed in the design of the craft.
> Then, they'd set the GA to work.
>
> When it got to work, it would generate a random sampling of designs,
> CHECK TO SEE HOW AERODYNAMIC THEY WERE, and prioritize the designs
> which were the most aerodynamic in the next run, which would amount to
> random variations, breedings, etc. from the previous generation.
>
> So. GA. Trying to generate good heuristics. It generates a random
> sampling of heuristics (or sets of heuristics). Then it checks to see
> which heuristics are best, and prioritizes the best heuristics in the
> next generation.
>
> But how do you figure out whether a heuristic is good or not? Well,
> heuristics are rules for action. You USE the heuristic, and you see
> how well off you wind up. (Using some definition of "well off" which
> has nothing to do with motivations, I suppose.) In fact, just one
> trial run really isn't enough... you need to try using the heuristic
> many many times in order to even out statistical hiccups.
...so you have a second genetic algorithm, trying out different
heuristics on the first. And then, if neccessary, one above that.
Has this been tried? Meta-design? Meta-meta-design?
Martin
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