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Re: [computer-go] Modern brute force search



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Hi,

Whilst I agree with almost everything that you have been saying so far,
~ I just wanted to pick up on this point in your contradiction proof (and
I am not a chess/go programmer, so could well be missing something):

|  Even though  blacks 20 responses all  lose, white must  still have a
|  response for  each of  those 20 moves.   That means we  have already
|  branched to 20 different lines of play, all of them based on perfect
|  play by both sides.

This depends on your definition of "best line". Assuming that white can
always win, there are two sets of possibilities for this definition:

1) White wins and so black has no real "best move", (s)he therefore
plays as well as possible, but always knowing that a loss was inevitable
assuming that white plays perfect responses.

This would be a good strategy if there is a chance that white doesn't
know the correct response to all possible black moves. If not, black may
as well resign after the first move and so the single best line is
simply: White moves, black resigns.

2) Black does have a "best move". This could be based on a criterion
such as making the game last as long as possible before a loss, or
having as much material as possible when the game finishes (or some
other criteria). In this case, black also has a defined set of "best
moves" to follow, resulting in a single line of play (aside from some
coincidental cases where there _are_ equal results, however the
branching factor would be much, much lower).

Without either of these considerations, how can you define "perfect
play"? The only way that this could fit would be if all of black's 20
response moves have exactly equal outcomes, which also seems unlikely.

I know that you picked up this point by considering the case for only
one line that results in a draw, all others resulting in a white win,
but this extends beyond that situation.

This isn't really disagreeing with (any of) your point(s), I'm just
interested in your thoughts on this, and am happy to learn :o)

Joss
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