In message
<95be1d3b0911240657g24467ecey84cdb05918ca7...@mail.gmail.com>, Vlad
Dumitrescu <vladd...@gmail.com> writes
On Tue, Nov 24, 2009 at 15:45, Jeff Nowakowski <j...@dilacero.org> wrote:
On Tue, Nov 24, 2009 at 03:06:51PM +0100, Vlad Dumitrescu wrote:
So the only difference in play is when losing, one has to keep trying
to lose as little as possible, resigning isn't an option. When ahead,
there's no reason to try to win big, unless the goal is to reach a
certain amount of points in a certain number of games. (Programs
aren't greedy in the same way we people are :-)
Let's assume that the program will play for a gambler, and will play
many (an indefinite number) of independent games. Then I think "no
reason to try to win big" is wrong. The rational approach to gambling
is to maximize your expected value for each game.
Yes, but that doesn't necessarily mean that the strategy should be to
push each game to the limit. Trying to win with a large margin is less
safe than with a small one, so it depends on the gambler's mindset.
It's not a matter of "pushing .. to the limit", it's a matter of
maximising expected winnings. And it shouldn't depend on mindset, it
should depend on calculation.
Suppose my attempts to read the game tell me "If I seal off my territory
at A, I will win by 5 points. If instead I invade at B, then 70% of the
time I will win by 25 points, 30% of the time I will lose by 5 points".
If I am playing Go, I will prefer A. If I am playing bang neki, I will
prefer B.
Nick
So now the problem
becomes harder -- you have to realistically guess the risk vs reward
over a spectrum of points.
And also possibly add knowledge about the opponent(s).
I think this game is clearly more difficult than a binary win/loss
game.
This is exactly my opinion, too.
regards,
Vlad
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Nick Wedd n...@maproom.co.uk
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