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Anyway I decided to split the Numfield populations into two leagues. The champions league only contains the very best strategies. Of course due to the environmental effect, putting the best strategies into a separate pool watch them and see what happens. Pools also speed the simulation speed up considerably. Also it might be more appealing to newcomers if they could introduce their babies in less hostile environment. Hey, aren't there any newcomers? Well, why Joes and my strategies look so good. Because we both spent lots of time working on them. I guess one had do be fairly good to beat our top strategies, but look at our early experiments, do your early experiments compete with them? I guess the do!
Well, why are environments are so hostile anyway? Numfield was intended as a cooperation experiment. But, what happened? The richer set of possibilities (in comparison with the prisoners dilemma) and the interaction between all players at once, seems to make lots of learning necessary to adjust opponents behaviour. And when I manage to learn to predict the opponent. Why use it for cooperation, when I can use it to beat him? Thats what seems to have happened...
Long term observation show that the success of the latest strategy is considerably blocked by the presence of those highly randomized strategies like Random11 and PseudoRandom12. Seems that those learning ones have problems adapting to random behaviour.
BTW in case there will me more contestants somewhere in the future might had to limit the number of introduced strategies per player to s.th. like 2 or three per pool. One reason for this is the environmental effect demonstrated in more detail on the Pi Experiment Page.
If you have any other question, wishes or ideas, strategies or even class files please send an email to dorisnfrank@bigfoot.com.
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