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Subject: Re: BGN's "no-time" argument soundly refuted

Author: Robert Hyatt

Date: 10:54:16 05/08/01

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On May 08, 2001 at 13:21:07, Wayne Lowrance wrote:

>On May 08, 2001 at 12:16:19, Robert Hyatt wrote:
>
>>On May 08, 2001 at 11:57:07, Larry Proffer wrote:
>>
>>>On May 08, 2001 at 11:43:29, Uri Blass wrote:
>>>
>>>>On May 08, 2001 at 10:58:01, Larry Proffer wrote:
>>>>
>>>>>
>>>>>Thank you for your reply. I concur.
>>>>>
>>>>>What we do know is that Fritz and Junior are, to all intents and purposes
>>>>>'equal', or very nearly 'equal'.
>>>>>
>>>>>If we need to find a winner, it makes *no* difference how many games we play.
>>>>>
>>>>>If we play one game, Fritz has a 50% chance, Junior a 50% chance.
>>>>>
>>>>>If we play one thousand games, Fritz has a 50% chance and Junior has a 50%
>>>>>chance.
>>>>>
>>>>>Number of games is not relevant when they are so closely matched.
>>>>
>>>>I guess that the number of games is relevant and if the number of games is
>>>>bigger the better learner is going to win and it means probably that Fritz is
>>>>going to win after many games because Fritz has a bigger book so it is more easy
>>>>for it to learn to go for lines that the opponent does not understand.
>>>>
>>>>Uri
>>>
>>>1. This, of course, opens up a lot of questions as to why machines were switched
>>>after a few games. This would have killed Fritz's learn files.
>>
>>Why?  Everything could have been moved easily.
>>
>>
>>>
>>>It is known that 'book-learning' can have bad effects, particularly after a
>>>string of losses. The effect can be to push the program away from its usual
>>>openings into even worse areas of the book. The desire, of course, is to hope
>>>that it gets pushed away from the losses towards soemthign less bad, but, in
>>>practice, it can be pushed into even worse regions from which there is no
>>>escape.
>>
>>
>>I don't know "where this is known" from..  If you lose a game with a specific
>>opening, and you don't play it again, you won't lose that game again..
>>
>Bob, I think that I have at times destroyed book lines for normal time controls
>by playing blitz and bullet with losses. But these lines may be perfectly sound
>for long time controls. I do not know this to be fact.


Fritz took the book learning algorithm from Crafty, including the code that
adjusts the learning value based on the rating of the opponent _and_ the search
depth reached during the game.

But in the case mentioned, there were _no_ blitz games of any kind played,
just the qualifying games.

>
>Also another thought. Consider two opening main lines a.) Line (a) is in fact
>better than line b). But against a better program line (a) loses, _not_ because
>it is a bad line, it just lost. Maybe line (a) was playing a superior cpu, a
>superior program and it lost.
>
>Opening line (b) is inferior to line (a) stipulated and will loose even worse
>but now both of the lines, as I understand are Kaput.
>>

Not sure what you mean by "kaput" but not in Crafty, normally.  IE a bad result
out of book isn't enough to kill a line.  It might remove the last couple of
choices in that line, but not the entire line...  unless you have a very tiny/
narrow book.

Against a "better opponent" my book learning takes this into account, assuming
the ratings are provided (this is automatic on a chess server)...



>>
>>>
>>>Books are so large, and the pathways produced by learning so unpredictable, that
>>>this effect is quite common.
>>
>>I have been doing "book learning" for 5 years now.  I don't see this at all
>>and I have a big book.
>>
>>
>>>
>>>So another question is why carry out a machine switch whose effect would have
>>>been to kill the learnt data?
>>>
>>>
>>>2. We know about learning in computer chess. Would you tell us if it (comp-comp
>>>learning) has any relevance at all in 'finding the best opponent for Kramnik'.
>>>Doesn't the luck involved with this bi-program learning process (remember, the
>>>learning pathways are almost infinite - we don't know where they lead, and they
>>>may make things worse) just add to the general fact that Fritz still has 50%
>>>chance, and Junior still has 50% chance?
>>
>>Learning is part of the engine.  In a match vs a human, a computer had _better_
>>have good learning skills or it will lose the same game over and over..



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