This is the problem with Go. "Branching factor".

9x9=81,
81 x 80 x 79 = 511920 positions to check.

You should try to search for "more likely" moves. Ex:
A1 is definetely not a first move. Any move at first
row/column will not be a good move, at least for the
first 5 or 6 moves.

So, just to ilustate:

lets exclude the first row/column in the firsts moves.

7x7 = 49 
49 x 48 x 47 = 110544 moves to check.

That means: 79% improvement ONLY removing first
row/column.


As a rule of thumb: avoid optimizing functions like
floodfill in the beginning. You should focus on
algorithm speed but at logical level. ( calc of
function O() ) .. sorry i don't know how is that
called in english. Perhaps someone could help.

The problem is that you are looking at a lot of
positions, and how that grows on each move deep you
add to the search. 
On every player move, you are multiplying by 81 the
time spend so far, try to lower that number, the
"branching factor".

Eduardo


--- Wodzu <[EMAIL PROTECTED]> escribió:

> Greetings guys.
> 
> Ive implemented standard minimax algorithm but is so
> enormous slow even on
> 9x9 board. For example when depth = 3 (player1 move,
> player2 move, player1
> move) computing time at the begining is like 1
> minute.
> I know that I should implement alpha-beta pruning
> variation to speed up it
> but what else can I do?
> I am eveluating position by using floodfill metod so
> for every single
> evaluaton i need to copy entire board. Ive heard
> that there is a
> possibility to store the board and not using
> floodfill to often by
> remembering what has changed and to just undo such
> changes but i cant
> figure it out by myself. Any faster way than
> floodfill to check the teritory 
> and catched stones?
> Thanks for any tips,
> 
> Regards. 
> 
> _______________________________________________
> computer-go mailing list
> computer-go@computer-go.org
>
http://www.computer-go.org/mailman/listinfo/computer-go/
> 


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