Moti ezra a écrit :
> Hi,
>
> I am using an alpha beta cutoff minimax search tree to play
> Othello (Reversi).
>
> I am trying to get my software to challange itself by having one
> player
> running the algorithm up to depth 5 and the other player up to depth
> 9-10
> Suprisingly the 5 depth player wins big time (exactly same
> implementation)
>
> Is this normal behavior when working with search trees (after all the
> other player is not optimal and cange change intended results) or do I
> have a bug lurking out there?
On a single game everything is possible, but if you did your experiments
on several games (from various openings or starting positions), a deeper
search should give better results, particularly when playing Othello.
Your results may be caused by a bug or by a poor evaluation function.
Note that for a random evaluation function, deeper searches give better
results in several games including othello, so if the problem is in your
evaluation function, it means that it is worst than a random one.
> Could it be that I will consider limiting the depth just to take
> advantage?
No. Searching deeper is very important at Othello. Current strong
Othello programs use selective searches to favour deeper search. In
Othello this is particularly important because a deeper search means a
sooner endgame, where the score could be exactly evaluated. On modern
hardware (say a 3GHz CPU), in 10 minutes games, strong programs usually
play perfectly when 25-30 empty squares remain on the board. In midgame,
Othello may suffer from "diminishing returns", ie searching deeper is
not so useful. However I think the problem arise at depths around 20,
not 5 or 10.
--
Richard
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