[computer-go] IEEE Spectrum article by Deep Blue creator

[Phil G]

> The null move test is to play 2 moves in a row for one side and consider
> the result an upper bound.  (or conversely to consider the result a
> lower bound for the other side.)


I take it that without a good evaluation function to distinguish the value of a move with other moves one or two ply down into the tree, especially in the early game, that null move prune is ineffective for pruning the tree. And worse, if the evaluation function is wrong.
 
Also, is it just me that a good evaluation function early in the game is difficult to write? 
 
On a slight different topic, for those of you with experience writing an evaluation function for an alpha-beta search, do you use the number of total moves played to weight different parts of the evaluation function? For example, it is easier towards the end of the game to know the certainly of certain points and use that as the evaluation function. But at the beginning of the game, an estimate of territory seems to be a better function (in light of not knowing the certain of any or few points). How do you merge these functions as the game transitions between middle game to end game? (and as different parts of the board are in various stages too).

Phil
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