Author: Ralph Stoesser
Date: 14:27:06 07/01/03
Go up one level in this thread
On July 01, 2003 at 17:08:29, Marc van Hal wrote: >On July 01, 2003 at 16:17:37, Magoo wrote: > >>On July 01, 2003 at 16:02:14, Albert Bertilsson wrote: >> >>>On July 01, 2003 at 15:55:07, Anthony Cozzie wrote: >>> >>>>On July 01, 2003 at 15:42:42, Albert Bertilsson wrote: >>>> >>>>>>Yes, but things are different with chess. In backgammon, you don't need to do >>>>>>deep searches. Backgammon is a randomized game, chess is not. There have been >>>>>>attempts, but not that succesful, i have looked at KnightCap, which uses >>>>>>standard minimax with a ANN to evaluate the quiet positions.It has a rating of >>>>>>about 2200 at FICS... pretty good, but no way near the top. I guess a program >>>>>>with minimax only counting material would have a rating near that. Like they >>>>>>say, chess is 99% Tactics. Nothing beats deeper searching. >>>>> >>>>>2200 on FICS with MiniMax counting material only? >>>>> >>>>>That is crazy! >>>>> >>>>>One of us is wrong, and hope it isn't me because I've spent many hours on my >>>>>engine and it still is now way near 2200 in anything other than Lightning! If >>>>>you're right I'm probably the worst chess programmer ever, or have missunderstod >>>>>your message completely. >>>>> >>>>>/Regards Albert >>>> >>>> >>>>Your engine, being new, still has a lot of bugs. I'm not trying to insult you; >>>>it took me a full year to get my transposition table right. At least, I think >>>>its right. Maybe. Anyway, the point is that it takes quite a while to get a >>>>good framework. I suspect on ICC a program with PST evaluation only could get >>>>2200 blitz. (with material evaluation only it would play the opening horribly, >>>>e.g. Nc3-b1-c3-b1-c3 oh darn I lose my queen sort of stuff) >>>> >>>>Anthony >>> >>>I agree that PST evaluation with Alpha-Beta and a transposition-table can play >>>at least decent chess, but that's quite many powerful improvements over MiniMax >>>with Material only. >>> >>>/Regards Albert >> >>I said near, and when i say minimax, i really mean alphabeta (no one uses a >>straightforward minimax). When my engine was "born" (minimardi) it had only >>material evaluation, searching 4 ply, it could play a decent game. Rated around >>1700 blitz at FICS. Now, consider searching around 8 ply, i think a rating >2000 >>is not hard to imagine. My point was that in chess, the most important thing to >>accuretly evaluate positions is a deep search. No matter what methods you use, >>if you search deep your program will play decent. This is one of the reasons why >>ANN have worked so well in backgammon and not in chess. > >Can't neural networks look deep ? >Why is that? >And do neural networks learn or not? > >Marc No to the first question in any case and no to the second question in respect of Snowie backgammon. NN backgammon programs like Snowie are looking max. 3 ply ahead and evaluating the 'MiniMaxed' positions with a pre-trained NN. They do not learn anymore while playing, but it would be also possible to do so.
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