Benoit St-Pierre,  wtorek, 24 czerwca 2008:
>Hello,

>So we should aim at a solution that relies more on structure than feedback.
>A better idea for Scid would be classify the exercises according to the kind
>of material configuration : pawn structure and piece distribution.  
This makes sense for some special positional exercises and maybe for some 
endgame database. This isn't a general solution - for example, it doesn't 
help for tactics.

>We should not rely on manual classication, but something like pattern
>recognition.  Manual classification is expensive and error-prone : just look
>at the mess with bibliographic keywords.  
>?  Tags are practical, but unreliable.  They should stay at the personal
>level.  Nothing very original here : I am only hinting as to why expert
>systems did not fulfill the hopes classical AI entertained about them.
IMHO only manual classification makes sense for most databases. Anyway I will 
leave classification to database creator. If it is done by custom PGN tags, 
it can easily be added automatically by external tool if classification for 
given database makes sense.

>Anyway, the biggest problem, IMHO, will be with the headers.  Chess database
>are organized around real games.  Exercices based on real game can provide
>information.  We just have to decide how to tell the user that it's just a
>game fragment in the game list.  (Suppose we have 10 exercises out of a 
>single game.)  
Why not give original game headers?

>But for endgame, that is already more difficult.  How are we
>to indicate that it's the Vancura position we are practicing ?   A line with
>question marks is very uninformative.  Maybe we should think about this,
>while thinking about the normalization of header information.
Custom tag 'Vancura position' is best for me. It allows both easy studying  
and training. For training you may practice only Vancura position or all rook 
endgames in database - then you won't be given tip about Vancura position.


-- 
Michal Rudolf

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