Author: James Robertson
Date: 10:35:50 06/12/99
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On June 11, 1999 at 18:58:09, Dan Homan wrote: >On June 11, 1999 at 17:43:59, Jon Dart wrote: > >>On June 11, 1999 at 10:39:13, Dan Homan wrote: >> >> >>>I've been thinking about this alot recently. One thing that occurred >>>to me is that this might be an effecient way to create a neural net based >>>program. >>> >>>Say the neural net (nn) is responsible for filling a piece-square table... >>>Then the nn could operate either once, at the root of the search, or >>>only selected times during the search. This would largely overcome >>>the major drawback of nn evaluations which is that they are slow. >>> >>>Then we could have a TD based learning program that also learns >>>evaluation features! >>> >>>I've thought alot about building my next chess program on this >>>idea.... The one major drawback that I see is that there will be >>>a relatively large number of parameters for learning to adjust. >>>The other drawback is that I really know nothing useful about >>>programming neural nets. :) >>> >>> - Dan >> >>KnightCap (http://samba.anu.edu.au/KnightCap/) has learning of >>its evaluation parameters (as well as book learning) .. it >>appears to work very well. But I don't believe it does non-leaf >>evals. > >I've read the knightcap papers. I was thinking it might be interesting >to go a step beyond learning values for pre-defined evaluations features >and actually learn new features not previously defined. > >Neural Nets will allow this, but they are slow.... so I was thinking >of using a neural net to fill piece-square tables at the start of the >search or at well-defined points in the search. Maybe this wouldn't >work, but it is interesting to think about. > > - Dan >> >>--Jon I am fascinated by program's learning, but I know nothing of neural nets or any other learning feature. Where can I find more information? I am too lazy to fine-tune my program's eval by hand. :) James
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