Author: Marc van Hal
Date: 07:46:03 07/02/03
Go up one level in this thread
On July 01, 2003 at 17:27:06, Ralph Stoesser wrote: >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. What is neural networks if it does not learn by it self? (a bugy program?) And again: Why can't it look deep? I think real A.I. can not have these problems. Marc
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