Author: Vasik Rajlich
Date: 02:20:56 05/01/04
Go up one level in this thread
On April 30, 2004 at 10:43:01, José Carlos wrote: >On April 30, 2004 at 08:54:55, Anthony Cozzie wrote: > >>On April 30, 2004 at 07:26:55, rasjid chan wrote: >> >>>On April 30, 2004 at 06:59:15, Uri Blass wrote: >>> >>>>On April 30, 2004 at 04:27:23, rasjid chan wrote: >>>> >>>>> >>>>>The Secret of the Commercial Chess Programmers IMNSHO. >>>>> >>>>>Omid mentioned Falcon reached 2600 after improvements in search and >>>>>now he runs out of ideas to push search further and had to try >>>>>to improve on his eval. Again eval would reach a barrier as most >>>>>programs with 2600 has a very good eval and the eval curve again >>>>>shows diminishing returns for code-increase / additional factors. >>>>>The only way is to be able to have a vertical upward displacement >>>>>for this eval-curve which is basically logarithmic - it may be +100 elo >>>>>by just using the correctly tuned weights. >>>>> >>>>>The Deep Blue team mentioned they used MLR and since it can be done, >>>>>it means it should not be too difficult as MLR itself is not very high >>>>>mathematics. I used MLR before and has a not-yet-complete idea of using >>>>>it to tune weights. >>>>> >>>>>The requirement is we need a collection of say 100 drawn game-files, the >>>>>more the bettter as reading and applying eval() at all nodes for a 1000 >>>>>games files may just take a second more. >>>>> >>>>>MLR tuning is logically based and it should not be too bad, at least >>>>>we have some indications, but again we may not know it could be the BEST >>>>>way to do weights tuning. Also it has a very high return if it works. It is >>>>>a one time investment and once the tuner is written and we keep the >>>>>100 game-files, it could be re-used anytime we change our eval(), we only >>>>>need 10 mins to do a rerun and we have all the weights re-tuned and we >>>>>never need to worry too much what weights we assign when we add a >>>>>new factor. >>>>> >>>>>The following is what I arrive at on first thought, it may be triple dumb! >>>>> >>>>>MLR is about finding a set of constants c0,c1,c2... for >>>>> >>>>>Y = c0 + c1*X1 + c2*X2 + ..... >>>>> >>>>>As I have not think it through completely, others may be able to >>>>>complete the picture and let's see if it can be done easily. >>>>> >>>>>MLR requires us to collect a set of table data : >>>>> >>>>>per row: >>>>> >>>>>Y , X1, X2, X3,...., Xn >>>>> >>>>>a row/more is added to the table after applying our tuner to list thru the >>>>>game-files and making the moves and apply score = eval() to the >>>>>"neutral nodes". >>>>> >>>>>scheme 1:- >>>>>Y is the should-be-near-zero score. >>>>>Xn is our current weights used. >>>>> >>>>>scheme 2 - a "dumb" improvement :- >>>>>Instead of using Xn we use del_Xn,the change in Xn alone(when only Xn is allowed >>>>>to change) needed to make score == zero. >>>>>After computing all del_Xn, we use >>>>>Y = score = eval() using Xn + del_Xn instead of Xn. >>>>>This may be better as weights not activated in certain nodes >>>>>will have del_Xn = 0; >>>>>Is this scheme ok ? >>>>> >>>>>Also in general for MLR, Y and Xn in should be scaled using a >>>>>weighted average. Most common weights may vary about a certain mean value. >>>>>Nodes should also be weighted, the nodes that eval() to far-from- >>>>>zero are given less emphasis/weights/rows as the games are supposed to >>>>>be drawn games. >>>>> >>>>>After running MLR, we obtain solution to >>>>>c0,c1,c2... etc and this enables us to compute the optimal change >>>>>needed to our weights. The correlation coefficient R2 from MLR may indicate >>>>>how reliable the proposed changes is, or it may throw some lights >>>>>on the quality of our eval(), etc. >>>>> >>>>>Also recording how often a factor is activated on average can let us decide >>>>>if it may be discarded or used with a more conservative weight. >>>>>MLR may also give us other indications when we may know certain factors >>>>>are not important/or unstable when the tuned weights indicate an >>>>>exceptionally high change needed, ie the weight or the factor itself may be >>>>>suspect and should to be discarded. >>>>> >>>>>Should I do it now when my program is at 1900 ? >>>>> >>>>>Rasjid >>>> >>>>No >>>> >>>>I believe that Crafty never used MPL and it is clearly better than 1900. >>>> >>> >>> >>>>I also believe that the secret of Shredder is mainly better search than Crafty >>>>and not better evaluation(I do not say that it does not have better evaluation >>>>but I guess that most of the rating difference between Crafty and Shredder is >>>>because of the fact that Shredder has a better search). >>> >>>Not much dispute. But we know one thing. After a commercial chess program >>>reaches ELO 2600+, you either tell the author he's redundant or we can >>>imagine he goes all way to to seek even little improvements... like someone >>>testing with 2/3 computers running for days/weeks(months ???). >>> >>>Top programs must be top in BOTH SEARCH AND EVALUATION - no short cut >>>as none have suggested that one can completely replace the need for the >>>other, or even that we can have one very good and the other plain and >>>simple. >>> >>>But if my guess is correct, and if MLR tuning works good, then it is >>>HIGHLY BENEFICIAL as a one time investment. Commercial chess programmers >>>have been on their programs for years and my guess is they should have >>>tried MLR tuning, at least to see if it is reliable. >>> >>>I see MLR tuning may not be difficult and I definetly would spend a few >>>weeks to test if my program ever reach ELO2500 >>> >>>Rasjid >> >>Don't feel bad about Uri. He begins all his posts with "no" :) > > > No. > I can point at least one message where Uri didn't begin with "no", so your >statement is false. > :) > > José C. > No. I do not understand it. Just because Anthony says that Uri always starts his posts with the word "no", doesn't mean that there can be no posts from Uri which do not start with exactly no. It is enough that there is something similar to no somewhere near the beginning. I do not believe it, that showing one message would give a contradition to the original claim. Vas :-) > >>BTW, if your program is rated 1900, you almost certainly have bugs. IMO >>2200-2300 ICC rating is the "more-or-less-bugfree" zone. That is with a basic >>eval, searching 9-10 ply with null move, PVS, killers, history, transposition >>table, etc. >> >>anthony >> >>>> >>>> >>>>Uri
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