Hi Vincent,diep wrote:hi Scotti, If you're so interested, why don't you do it the Frans Morsch/Chrilly Donninger way?
and what would be the point of going that way?!?
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Hi Vincent,diep wrote:hi Scotti, If you're so interested, why don't you do it the Frans Morsch/Chrilly Donninger way?
Perhaps refers to look at the code assembly other programs?mjlef wrote:What is the "Frans Morsch/Chrilly Donninger way"? I am sorry if I missed something.diep wrote:hi Scotti, If you're so interested, why don't you do it the Frans Morsch/Chrilly Donninger way?
Vincent
The Database would probably become quite big:Thomas Gaksch wrote:Hi Alessandro!
wow, great work. I think your research is a very good starting point.
I personally believe that Rybka and/or Fritz are going one step further. I think they have not only informations about the "pure" material imbalance but additional informations about the pawn structure (or something else). For example you have calculated the probability of the RPP against RPP (rel(w)=1.02, abs(w)=0.51, rel(X)=1.00, abs(X)=0.50, mat=0, count=4156, R=1.00 / RPP rpp ()) as a draw. But if white for example has a double pawn and black has a connected passed pawn then the probability that black wins is much greater. So if it would be possible to calculate such relations and store them in a big hashtable it would be a great improvement for the evaluation.
Thomas
Hi Thomas,Thomas Gaksch wrote:Hi Alessandro!
wow, great work. I think your research is a very good starting point.
I personally believe that Rybka and/or Fritz are going one step further. I think they have not only informations about the "pure" material imbalance but additional informations about the pawn structure (or something else). For example you have calculated the probability of the RPP against RPP (rel(w)=1.02, abs(w)=0.51, rel(X)=1.00, abs(X)=0.50, mat=0, count=4156, R=1.00 / RPP rpp ()) as a draw. But if white for example has a double pawn and black has a connected passed pawn then the probability that black wins is much greater. So if it would be possible to calculate such relations and store them in a big hashtable it would be a great improvement for the evaluation.
Can someone suggest a nice, freeware stats package that can do coorelation analysis,and curve fitting? The data is really great, and in tests my program finds a match with specific material imbalances in around 20% of positions searched. I suspect many of the other positions have such a huge material difference that they are not important, but it would be nice to figure out how to best use this data. I would love to do some coorelations, so let me know what you think would work best. Come on all you statisticians!Alessandro Scotti wrote:Hi Thomas,Thomas Gaksch wrote:Hi Alessandro!
wow, great work. I think your research is a very good starting point.
I personally believe that Rybka and/or Fritz are going one step further. I think they have not only informations about the "pure" material imbalance but additional informations about the pawn structure (or something else). For example you have calculated the probability of the RPP against RPP (rel(w)=1.02, abs(w)=0.51, rel(X)=1.00, abs(X)=0.50, mat=0, count=4156, R=1.00 / RPP rpp ()) as a draw. But if white for example has a double pawn and black has a connected passed pawn then the probability that black wins is much greater. So if it would be possible to calculate such relations and store them in a big hashtable it would be a great improvement for the evaluation.
I'm not sure those exceptions can be properly analyzed in a statistical way, unless the number of games sampled is really huge (or some method is used to produce more samples for the "interesting" configurations). Some experts in statistics would be able to answer better though, when I first heard of Monte Carlo I could only think of the F1 GP!
For now I think it's difficult enough to figure out how to improve evaluation of material, which is the main goal of this research. Exceptions like doubled pawns or connected passers can be accounted for in the evaluation function so this information is usable in all situations. In fact, at present I have only generated statistics about 1100 or so imbalances, not a very big number.
This link does not work for me, i get a "not available" error message ...Alessandro Scotti wrote:Like many, I think, I have often wondered what could be the secrets of Rybka. One particular feature that was often hinted at and seems to be indirectly confirmed by the fact that Larry is now part of Rybka's team, is the precise evaluation of material imbalances.
The original article by Larry Kaufman, a highly recommended reading, is here:
http://mywebpages.comcast.net/danheisma ... alance.htm
A short while ago, I decided to do some investigation on my own and tried to reproduce Kaufman's experiment, but this time with the help of some tool. For me, modifying Kiwi was an obvious choice since I know the code well and Kiwi includes a robust PGN parser.
What I'm trying to do: analyze and collect data for material imbalances over a large collection of games, and use the data for... something! Ideally, a chess engine will use the data to properly evaluate the material situation on the board, rather than relying on values that are good but only "on average".
But first, the data. I have put everything on this page:
http://www.ascotti.org/programming/chess/mat_stats.html
Interpreted data, statistics and source code. Sorry to put on external link but the HTML page alone is well over 100K.
Now for the help request! I have several questions...
1) what do you think of this approach?
2) can you spot some mistake or need more information?
3) if the approach is good, what could be a good way for an engine to use this data?
Of course all of this is free to use in any engine, I really hope we can make this approach work!