Author: Ricardo Gibert
Date: 22:36:37 05/27/02
Go up one level in this thread
On May 26, 2002 at 19:46:54, Robert Henry Durrett wrote: >On May 20, 2002 at 15:41:47, Eric Baum wrote: > >>On May 20, 2002 at 15:05:15, Russell Reagan wrote: >> >>>I would bet that a program with an evaluation function that primitive wouldn't >>>break the 2000 elo mark, or maybe between 2000-2100 at best. Of course I could >>>be wrong and someone like Bob or Dan Corbit could tell you better the >>>differences between a program with a simple evaluation function vs. a program >>>with a complex one, >> >>Hopefully one of the experts will respond :^) >> >>>There are programs like this, and they do learn new features. They generally use >>>neural nets or something like that. They also generally stop improving at about >>>a beginner level. >> >>I'm only interested in ones that actually do better... >> >>> >>>>Also, for comparison, does anybody have a recent estimate of rating >>>>point gain per additional ply of search? >>> >>>I don't, but someone does I'm sure. I would guess however that at some point you >>>aren't going to get many more rating points, and then once you reach a really >>>deep depth, you will start to see more jumping up of the rating, then another >>>diminishing returns area, then another jump, and so on, until you reach a ply >>>depth where you solve the game. >> >>Hsu used to give talks graphing rating increase vs ply and claimed something >>like a 200 point increase per ply (I'm just going from memory, so number might >>be in error). He used to claim, I think, that this increase would continue >>to arbitrary depth. (Of course, he was trying to convince IBM management to >>continue funding development of his parallel machine, but subsequent events >>lent some credence to his previous prognostication.) >> >> >>>And since I don't even know what "context dependent forward pruning" is, maybe >>>you could explain that :) >> >>What I mean is some method of doing something like what humans do: >>deciding to pursue some lines of search and abandon others, based on the >>board position. > >When people talk nowadays about "forward pruning," are they doing that only at >the start position prior to search, or do they also do this at later points in >the search? Intuitively, it seems there would be a tradeoff between the time >required to do additional position evaluations [later in the search] versus the >improved quality of the rationale for additional pruning. In other words, a >series of pruning activities might give the best evaluation tree following the >original position to be evaluated. http://www.ginko.de/user/volker.pittlik/schach/lexikon/What-is-Forward-Pruning.html http://www.isr.umd.edu/TechReports/ISR/1993/TR_93-57/TR_93-57.phtml http://www.seanet.com/~brucemo/topics/nullmove.htm > >>Logistello, for example, does additional pruning beyond >>alpha-beta in Othello, and the Deep Blue crowd tried singular extensions, >>but again the singular extensions never added much to their ratings either. >>These were forward pruning methods, but didn't really look at the board >>position, really only looked at the evaluation of the board and evaluation of >>other lines >>to make a decision what to prune. So singular extensions prunes when one line >>is much more highly evaluated than others, independent of what the actual >>positions are, but my understanding is SI didn't lead to much gain. Is there any >>serious forward pruning going >>on, leading to real ratings improvements? And if so, is anybody gaining >>from pruning based on position as opposed to merely numerical evaluation?
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