Author: Vincent Diepeveen
Date: 11:46:18 08/04/02
Go up one level in this thread
On August 04, 2002 at 14:06:55, Sune Fischer wrote: will, believe, think, consider. Please proof it. chess is very simple compared to other applications where automatic tuning is supposed to work in the future. So far i have not seen a single decent program that can do better with automatic tuning than without. there is a shitload of freeware programs and volunteers to rewrite them to enable automatic tuning. Please pick a strong program and tune it. I would advice crafty. A small parameter set. Even big advantage for the tuners, but already a good program to start with. Finding the best values as a human isn't trivial. It sure isn't for programs. But humans use domain knowledge your tuner doesn't. >On August 04, 2002 at 13:26:05, Vincent Diepeveen wrote: > >>On August 04, 2002 at 11:47:01, Sune Fischer wrote: >> >>>On August 04, 2002 at 09:13:31, Vincent Diepeveen wrote: >>> >>>>On August 01, 2002 at 05:16:55, Sune Fischer wrote: >>>> >>>>We must not think too simple about autotuning. It is a complicated >>>>matter. Yet the obvious thing is that the autotuner has no domain specific >>>>knowledge. >>>> >>>>So suppose that someone *manages* to find a good way of tuning. >>>> >>>>Even the simple evaluation of deep blue, which had about a few tens >>>>of patterns and each pattern indexed by an array or so from 64. >>>> >>>>We talk about 5000 adjustable patterns (i like round numbers good) or >>>>so for an average program. >>>> >>>>to tune that in the incredible good >>>> O (n log n) that's like (using 2 log) >>>> >>>>==> 5000 x 12 = 60000 operations. >>>> >>>>Each operation consists of playing a game or 250 at auto player. >>>>No commercial program ever managed to improve by playing blitz... >>>> >>>>250 games x 60000 = 15 000 000 games. >>>> >>>>Get the problem of learning slowly? >>> >>>No, TDLeaf is a steepest descent algorithm, if it works it will go much faster >>>because it's going directly against the gradient. >>>I'm not saying it will be easy, or that it won't require a large number of >>>games, but I believe its potential is greater than what is humanly possible. >>> >>> >>>>Now we talk about a simple thing called chess, just 64 squares. >>>>If i autotune something to drive my car there are a zillion parameters >>>>to tune ;) >>> >>>Yes, but you tune them _all at once_ so it's really not that bad :) >> >>Exactly the answer i wanted to hear. This is simply impossible to tune >>them all very well at once without domain knowledge. If you get a perfect >>tuning at >> >>O (n log n) you already get a nobel prize. > >Well I wouldn't count on it :) >Deepest descent can train hundreds of weights if the energy space is smooth >enough, just think of back propagation. >I believe this will be the case for a chess evaluator, linear forms, independent >variables, should be doable IMO. > >>The tuning we need, and definitely traffic, is not 'all a little tuned', >>errors are not acceptible simply. One parameter which is -1.0 instead of >>+0.22, that's an unacceptible error simply. Hand tuning is even >>more accurate. It even sees the difference between 0.22 and 0.40 very >>clearly. In case of the pro's, even the difference between 0.22 and 0.20 >>is getting felt in some cases (bishop vs knight). > >That could happen if they start off from random values, it would be a so called >local minimum. If they are initialized with the best known values they should >improve from there. > >>Obviously you won't achieve such accuracy under O (n log n) with TD learning, >>it's a rude and primitif algorithm which can be considered lucky if the plus >>and minus sign are already guessed right. > >With 5000 weights, then yeah you'll need 10000 games, but isn't that doable now >a days? You might see rapid improvement in the beginning, and then the curvature >diminishes and the process is slowed down. > >>The pro's are not far off perfect tuning nowadays. Of course the parameters >>can get improved, but definitely not their tuning. > >But how do you, as a human, find the best values? >You just sit there, watch it play and then go; hey it should have played e4 >instead of e3, so I better adjust... >How much do you adjust, and do you do this for all 5000 weights? >This ad hoc method sucks bigtime, plane and simple. >The pros are not doing it this way, I can't believe that. > >>I doubt you can achieve >>much better tuning with crafty too. > >If Crafty was a little easier to hack I would do it, but I can't even get it to >compile. (there is some stack space problem with the egtb.c). > >>It's programs like DIEP where tuning can be improved bigtime, but of course >>we talk about FINE tuning. Whether it's 0.023 instead of 0.020. >> >>In DIEP i work not at 1/100 of a pawn but 1/1000 of a pawn. Another 1000 >>horrors more :) > >Floats could be needed for this, integer calculation (even milipawns) do not >work well with sums of fractions... > >-S.
This page took 0 seconds to execute
Last modified: Thu, 15 Apr 21 08:11:13 -0700
Current Computer Chess Club Forums at Talkchess. This site by Sean Mintz.