Joined: July 2006
A familiar pattern emerges. ~33135 generations.
What I find amazing is that such a simple construct can get so close to the target despite hardly any, well, anything really.
I implemented the TSP a while ago also (still under wraps for now) and again this procedure works amazingly well.
1) Generate a random population.
2) Sort by fitness (route length for TSP, or score here)
3) Delete the bottom % of the population.
4) Recreate the same % from the rest of the population
5) Throw in the odd mutation
6) Rinse and repeat.
And from the mess comes short TSP routes. From the mess comes high scoring patterns.
I can see why the ID crowd has such a problem with this sort of model. I can't imagine a realistic analogue to a biological population, say of bacteria, where the least fit make room for the fitter and information is exchanged to create the next generation with the odd mutation.
Just not going to happen is it?
I also mentioned that He'd have to give me a thorough explanation as to *why* I must "eat human babies".
if there are even critical flaws in Gaugerís work, the evo mat narrative cannot stand