Author: Sune Fischer
Date: 08:47:01 08/04/02
Go up one level in this thread
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 :) -S. >>On July 31, 2002 at 18:10:08, Vincent Diepeveen wrote: >> >>>And he'll never do a competative chessprogram again either, he forgot to >>>add that too. >> >>It's the classic problem. Person A has spent 15 years on his chessprogram, he >>thinks he knows it all. In from the right comes a guy who knows nothing about >>chess programming but is very good a tuning weights in general. He applies his >>knowledge to a simple chess program and is very successful in increasing it's >>strength. >>Person A now concludes; "his method isn't working, his program is still weaker >>than mine":) >> >>>I remember Knightcap very well. TD learning had the habit to slowly >>>make it more aggressive until it was giving away a piece for 1 pawn and >>>a check. >>> >>>Then of course the 'brain was cleared' and experiment restarted. >>>So in short the longer the program used the TD learning the worse it >>>would play, from my viewpoint. >>> >>>Definitely from a chessplayers viewpoint it did. Of course we must not >>>forget that in the time it played online, that nearly no program was >>>very aggressive. So doing a few patzer moves was a good way to get from >>>perhaps scoring 11% to 12% or so. >> >>So in other words, if you teach it the wrong things it doesn't work? >>Why am I not surprised. >> >>-S.
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