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Subject: Re: note

Author: Vincent Diepeveen

Date: 06:24:58 07/07/03

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On July 07, 2003 at 07:14:39, Ralph Stoesser wrote:

I remember a time that in computerchess some very scientific university programs
won the world title.

That was when the programs could search like up to 9 ply or so.

Sincethen Rebel won the open world title and it was a PC program from then on.
This year the only scientific program joining at more than 1 processor will be
DIEP. however because there has been fulltime work performed at the engine for
quite some time and i doubt whether you can see it as only scientific.

Not using the money generating ICGA definition, but the time invested, then the
world title will be won by a pro for sure this year. It was like that the last
13 years too.

That is because they can earn their living creating a chess engine.

In short when search depths will go deeper a bit than they are now, and when it
would be possible to make a living selling a backgammon engine, then all the
amateuristic ANN crap will be gone for sure.

Note that sometimes you can only sell your stuff saying you do the same like the
competitor. I do not know to which amount that is the case in the wordings of
the backgammon people.

Just like Ed Schroder sold Rebel one day using 'anti-GM' feature. Until today we
do not know what it is, except that he denied it being a simple thing like
opening the position a bit more. It possibly is a commercial vehicle to sell
something already existing, that's all.

Note that other sports people claim that just search depth solved chess,
referring to deep blue. So i get impression you are the same type of guy in this
case.

>On July 07, 2003 at 05:50:43, Vincent Diepeveen wrote:
>
>>On July 07, 2003 at 01:49:50, Ralph Stoesser wrote:
>>
>>Go to an average backgammon tournament and you'll see in the top many
>>chessplayers there. of course don't try that in Greece. Not enough chessplayers
>>there. But even there the few chessplayers will be winning the tournament
>>nearly.
>
>Is this true for the very best bg players in the world, let's say for the top
>20?
>
>>
>>The doubling cube action is something that hand tuning will completely outgun of
>>course.
>
>It gets a bit offtopic since we are talking about backgammon all the time, but
>to clarify one thing about the cube handling: Accurate doubling cube action
>depends strictly on accurate evaluation of the related position. The math for
>the cube action _behind_ the board evaluation is relatively simple and for sure
>nothing for a NN based tuning, but as a precondition to calculate an accurate
>cube handling you need an accurate evaluation number of the current position,
>where evaluation number means the average outcome in winning points when playing
>the position in question infinite times. And in the field of evaluation of
>backgammon positions it has been found (so far) that NN based evaluation tuning
>does it better than hand tuned evaluation. This is obvious because otherwise the
>best bg programs would not do it NN based.
>
>greetings,
>Ralph
>
>>
>>You must compare it with casino games. As soon as there is a lot of money
>>involved all the chances there get written down by *hand* even. Also when it's
>>thousands of possibilities.
>>
>>Now in games of backgammon, a lot of money at the topboards is involved, but
>>that's because of people betting at their games, not getting paid for an engine.
>>
>>Cheers,
>>Vincent
>>
>>>On July 06, 2003 at 21:26:31, Vincent Diepeveen wrote:
>>>
>>>>On July 06, 2003 at 17:51:53, Ralph Stoesser wrote:
>>>>
>>>>>On July 06, 2003 at 17:38:01, Vincent Diepeveen wrote:
>>>>>
>>>>>>On July 06, 2003 at 16:21:05, Uri Blass wrote:
>>>>>>
>>>>>>>On July 06, 2003 at 15:42:25, Vincent Diepeveen wrote:
>>>>>>>
>>>>>>>>On July 06, 2003 at 08:00:48, Uri Blass wrote:
>>>>>>>>
>>>>>>>>>On July 06, 2003 at 03:04:07, Christophe Theron wrote:
>>>>>>>>>
>>>>>>>>>>On July 06, 2003 at 01:15:41, Uri Blass wrote:
>>>>>>>>>>
>>>>>>>>>>>On July 06, 2003 at 00:25:49, Uri Blass wrote:
>>>>>>>>>>><snipped>
>>>>>>>>>>>>>Maybe using it for the evaluation is not the most efficient use of a neural
>>>>>>>>>>>>>network in a chess program. It seems that the way human players manage to search
>>>>>>>>>>>>>the tree is vastly underestimated.
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>
>>>>>>>>>>>>>    Christophe
>>>>>>>>>>>>
>>>>>>>>>>>>I agree with you that search is underestimated in chess but I also believe
>>>>>>>>>>>>that search and evaluation are connected because a lot of search decisions are
>>>>>>>>>>>>based on evaluation of positions that are not leaf positions so you cannot
>>>>>>>>>>>>seperate them and say search improvement gives x elo and evaluation improvement
>>>>>>>>>>>>gives y elo.
>>>>>>>>>>>>
>>>>>>>>>>>>Uri
>>>>>>>>>>>
>>>>>>>>>>>I know that you did not try to seperate between them but my point is that if you
>>>>>>>>>>>want to do the same as humans in the search then changing the search is not
>>>>>>>>>>>enough.
>>>>>>>>>>>
>>>>>>>>>>>Humans may search position for some seconds and decide that this position is not
>>>>>>>>>>>good and later search the same position but decide that it is good for them not
>>>>>>>>>>>because they search deeper but because they learned to change their evaluation
>>>>>>>>>>>based on searching other lines that leaded to a similiar position.
>>>>>>>>>>>
>>>>>>>>>>>Uri
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>Well my point is just that when people talk about an application of ANN in chess
>>>>>>>>>>they always talk about implementing the evaluation with an ANN, or tuning the
>>>>>>>>>>evaluation with them.
>>>>>>>>>>
>>>>>>>>>>I think it tends to show that the application of ANN to chess has never been
>>>>>>>>>>done by a "real" chess programmer. Because evaluation is only a part of a chess
>>>>>>>>>>program. And maybe not the one that can be improved dramatically, or that needs
>>>>>>>>>>them in order to be improved. Personally I would not use ANNs in the evaluation
>>>>>>>>>>first, because I think they would be much more efficient somewhere else.
>>>>>>>>>>
>>>>>>>>>>On the other hand, you are right. If one could design an ANN to perform the
>>>>>>>>>>evaluation, it would be wise to use the same ANN (or an extension of it) to
>>>>>>>>>>guide the search.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>    Christophe
>>>>>>>>>
>>>>>>>>>I believe that the biggest advantage that can be achieved in evaluation is not
>>>>>>>>>in changing the initial static evaluation but in learning to change the
>>>>>>>>>evaluation during the game based on the results of the search.
>>>>>>>>>
>>>>>>>>>I also do not believe that what humans know is the target and the target should
>>>>>>>>>be better than what humans know.
>>>>>>>>>
>>>>>>>>>programs found better evaluation than humans in backgammon and program may find
>>>>>>>>>better search rules than humans in chess not because programs are smarter but
>>>>>>>>>because programs may do trillions of calculation to learn and humans cannot do
>>>>>>>>>it.
>>>>>>>>>
>>>>>>>>>Uri
>>>>>>>>
>>>>>>>>This is the same utter nonsense crap that i keep seeing AI people write. Yet on
>>>>>>>>average they even have less experience than you and keep believing in something
>>>>>>>>they can never proof to be made. If they would have even *toyed* with ANNs a bit
>>>>>>>>they will understand more about the impossibilities about it.
>>>>>>>
>>>>>>>I only say that I believe that it can be done.
>>>>>>>It does not mean that I know how to do it.
>>>>>>>
>>>>>>>>
>>>>>>>>Show me a backgammon program with an ANN that beats a 5 turns fullwidth
>>>>>>>>searching backgammon program :)
>>>>>>>>
>>>>>>>>Of course show it at a machine that you and i have at home.
>>>>>>>
>>>>>>>Very easy
>>>>>>>the 5 turns fullwidth searching backgammon program is going to lose on time
>>>>>>>every game.
>>>>>>>
>>>>>>>
>>>>>>>
>>>>>>>>
>>>>>>>>The average ANN expert is assuming he has to his availability something doing
>>>>>>>>10^1000 calculations.
>>>>>>>
>>>>>>>I am not ANN expert and I did not suggest ideas how to do it.
>>>>>>>
>>>>>>>>
>>>>>>>>That is the major problem when talking to these guys.
>>>>>>>>
>>>>>>>>Of course you can optimize an ANN for chess in 10^1000 calculations.
>>>>>>>>
>>>>>>>>But you will then be beaten by a database of just 10^43.
>>>>>>>>
>>>>>>>>I am however sure that 99% of all ANN interested will not understand what i
>>>>>>>>write here above, simply because they do not know the running time of the learn
>>>>>>>>methods applied. If they would read themselves into that, then less crap would
>>>>>>>>leave their mouth.
>>>>>>>
>>>>>>>I did not say that the learning methods that are used in backgammon can work in
>>>>>>>chess and it is possible that people need to invent different learning methods.
>>>>>>>Uri
>>>>>>
>>>>>>If there was money to earn by programming a backgammon engine, i am sure some
>>>>>>guys who are good in forward pruning algorithms like Johan de Koning would win
>>>>>>every event there. It's like making a tictactoe program and then claiming that
>>>>>>an ANN is going to work.
>>>>>
>>>>>Version 4 Professional edition, full version USD 380
>>>>>from http://www.snowie4.com/
>>>>>
>>>>>Do you know the rules of Backgammon? Remember, you have to consider two dices in
>>>>>your search tree. If it's so easy to do better without NN, do it and you will
>>>>>earn a lot of USD. Usually backgammon players have more mony in their pocket
>>>>>than chess players ;)
>>>>
>>>>There is so little backgammon players however.
>>>
>>>
>>>
>>>If you go to a backgammon
>>>>tournament i pay like 250 euro entry fee. it is sick. Every good chessplayer can
>>>>play backgammon very well trivially.
>>>>
>>>>It is a matter of a good % calculation and chances. this is trivial stuff.
>>>
>>>It isn't trivial. How do you explain that all top backgammon programs use NNs?
>>>Shouldn't be some trivial statistically calculation enough? In backgammon you
>>>have not only the problem to find the best move (what is also not trivially),
>>>but to find the right cube action for the doubling cube and that's very very far
>>>from beeing trivial. And why a good chessplayer should be able to play very well
>>>backgammon trivially? I would agree that it can help learning beackgammon to be
>>>a good chessplayer, but there is nothing like the implication you gave about it.
>>>
>>>
>>>If
>>>>there was to earn big bugs with just ENGINE (so i do not mean interface) then
>>>>there would be much chessprogrammers writing such an engine ;)
>>>
>>>Btw:
>>>Is there big bucks to earn with a chess engine?
>>>
>>>>
>>>>>Ralph
>>>>>
>>>>>
>>>>>
>>>>>>
>>>>>>As we have a saying here: "In the land of the blind, one eyed is King".
>>>>>>
>>>>>>That's why i focus upon chess.
>>>>>>
>>>>>>In contradiction to you, i know how to do it with ANNs (just like many others
>>>>>>do), i just don't have 10^1000 system time to actually let the learning
>>>>>>algorithm finish ;)
>>>>>>
>>>>>>Any approximation in the meantime will be playing very lousy chess...
>>>>>>
>>>>>>Hell, with 10^1000 runs, even TD learning might be correctly finding the right
>>>>>>parameter optimization :)
>>>>>>
>>>>>>TD learning is randomly flipping a few parameters each time. It's pretty close
>>>>>>to GA's in that respect.



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