Well it is an attempt to improve the playing strength, but that won't mean
that it succeeds.

What I do is the following(in short):
I have a trained move predictor model which consumes a board situation and
outputs beliefs for every playable move.
I want to use it to bias the search tree for the first N moves of a game
(opening phase).

So when tree search generates all legal moves, the predictor will score
them and only consider the best X move as legal moves.

It then should be forced to play "good" opening moves(of couse only if the
predictions make sense).

David


2013/6/24 Don Dailey <[email protected]>

>
> On Mon, Jun 24, 2013 at 7:58 AM, David Briemann <[email protected]>wrote:
>
>> I'm beginning to think that I didn't understand the tree search part
>> correctly. You say the tree search generates moves too. I thought moves
>> were only generated in playouts and the tree search part was to follow
>> already played lines until it reaches a position which has not been played
>> out. Probably that's the location were I have too look into.
>>
>
> I don't know the gory details of the implementation,  but clearly the tree
> portion of the search considers all moves (sooner or later) and much has
> been written about how MCTS is admissible - at least in theory.    That
> means it would,  if given enough time and memory,  play perfect go and will
> consider every legal move at some point.    But we know that playouts are
> not fully random and in many positions will only play a limited number of
> moves (perhaps just one) such as when defending atari.     So the search
> tree portion is not constrained by only what the next playout move will
> return.
>
> Read the code - and perhaps any documentation that comes with this
> program.   One this is clear to me though,  if you impose patterns
> non-probabilistically on the tree you will weaken the program considerably.
>     The reason MCTS works so incredibly well is that we have put patterns
> in their proper place,  as move guidance and not as a plausible move
> generator only.     The old style weak programs were heavily pattern based.
>     So I may be misunderstanding what you are trying to do - is this a
> study of some kind or a real attempt to improve the program?
>
> Don
>
>
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