> decades it has been understood that a chess program with a better > evaluation function improves MORE with increasing depth than one with a > lesser evaluation function so it appears that Go is not unique in this
Well, isn't that trivial? suppose, you have a "perfect" evaluation function, but you add a random value to each of it's evaluation values. Once your S/N value reaches 1/1, adding more probes/playouts will not yield a better signal. So you reach a "soft horizon": you got stuck in the fog. Adding false heuristics (cutting corners) such as pseudo-liberties, or don't-play-inside-own-territory may even worsen the case. IIRC this has been described before on the the mailinglist, when alpha/beta was still fashionable. AvK _______________________________________________ computer-go mailing list [email protected] http://www.computer-go.org/mailman/listinfo/computer-go/
