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Subject: Re: chess and neural networks

Author: Vincent Diepeveen

Date: 02:44:52 07/07/03

Go up one level in this thread


On July 07, 2003 at 01:49:50, Ralph Stoesser wrote:

>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?

i guess chessmaster sold 6 million copies and i do not know about chessbase but
all together they sell a lot of copies too. perhaps from fritz7 + fritz8 like
150000 or so?

>>
>>>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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