Author: Miguel A. Ballicora
Date: 12:43:49 08/04/02
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On August 04, 2002 at 15:24:50, Sune Fischer wrote: >On August 04, 2002 at 14:46:18, Vincent Diepeveen wrote: > >>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. > >Well, maybe you have, do you know how the pros are tuned? > >How can it be, that the pros have such a good evaluator, while you being an >FM(!), can't make something better? > >>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. > >It is a non-trivial exercise to do, and I don't know every character of >Crafty's code. Besides I would rather spend time on implementing this in my own >program and get an edge :) > >I believe I can make it work, maybe even improve on it. >It isn't real important to me whether you believe it works or not, I think you >should follow your ideas and I will follow mine, actually I prefer if you forget >all about TDLeaf as soon as possible :) > >>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. > >KnightCap was too interesting a project not to follow up on, I'm very surprized >it hasn't been done already. >To see people write that it doesn't work when a) KnightCap proved it _did_ work, >and 2) they have not even attempted it themselfs, is very funny to me. > >-S. 5000 parameters is not much when compared to the parameters needed to obtain the optimal conformation of a protein with a computer. In that case, it is almost impossible (with the current knowledge) to obtain the right conformation starting from scratch, but is is very doable when you start from the "optimal" conformation (determine by physical methods, not by a computer), you change something and see how the new conformation would look like. Iterations around the minimum are very fast because all the parameters behave almost linearly or close enough. When the parameters behave linearly the time to resolve the problem is O(1) (a linear regresion of n parameters is O(1)). So, even if they are not perfectly linear, it is way below n log(n). This might not be exactly like chess but it allows me to make this guess: I believe that learning methods will be useful to tune all the parameters when a new one has been introduced. I wonder how many parameters has been throw out in good programs just because they did not work, but they just needed a general fine tuning of all the rest. Regards, Miguel
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