Computer Chess Club Archives


Search

Terms

Messages

Subject: Re: chess and neural networks

Author: Vincent Diepeveen

Date: 18:26:31 07/06/03

Go up one level in this thread


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. 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 ;)

>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.



This page took 0.02 seconds to execute

Last modified: Thu, 07 Jul 11 08:48:38 -0700

Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.