Kramnik Ties Fritz; Machines Not Yet Our Masters
Maltov writes "World Chess Champion V. Kramnik ties his match against the software Fritz. Details here.
You can also check out a picture gallery and a short history of computer chess."
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If two chess players play perfectly, then the game will always result in a tie
Here's an interesting quote from MSNBC:
Friedel pointed to two weaknesses in Kramnik's play characteristic of humans. "Once in 200 moves a human will make a blunder, and that's all Fritz needs. And [Kramnik] was seduced by beauty." He added that Kramnik "understands 100 times more about chess than any computer, but tactically Fritz is a monster."
-- Kircle
The problem with this is that defining "perfect play" is next to impossible in chess. Different players have very different playing styles, and if player A is strong against player B, and B is strong against C then it doesn't necessarily mean that A could defeat C.
Computers are strong in tactical play, humans in positional; people have argued for ages, which is better, so far both styles have their proponents among grandmasters.
And we can't really find an answer to this question unless we compute the entire game tree of chess, but this is impossible, even if you used all the atoms in the Universe to track the nodes in your tree.
Btw, the concern that chess as a game will exhaust itself and in the future grandmasters will always tie, has been expressed many times in the past. So far they have all been proven wrong, usually when some prodigy (Tal, Fischer, Kasparov) has come forward and brought new innovations with him. Computer chess is in a similar position, bringing many new ideas to the chess world, and countless new chess theories have been created by analyzing how computers play.
So I am quite optimistic about the future of chess, there is certainly no end in sight for now.
When men used to be men
One oft-quoted complaint by Kasaarov, of the last man-vs-machine match against Deep Blue, was that Deep Blue was programmed with the moves of all of Kasparov's past championship games so it could ostensibly analyze the strategies used by Kasparov beforehand, while Kasparov was not allowed to look at Deep Blue's previous games.
Anyone know if this was ever an issue in this current tournament?
There's 10 types of people in this world, those who understand binary and those who don't.
Hello, sorry, but... Go has not been analyzed and picked apart enough for us to say that it us much more difficult than chess.
Perhaps with the belief among computer chess researchers that chess has been solved will Go soon undergo the same nitpicking that chess has
This game is much more popular than chess in China, Japan, and Korea. Somehow, you seem to assume that these regions are all completely deviod of any programming, AI, or mathematical talent.
These people are obviously just sitting around waiting for us Westerners to solve chess so we can move onto their little problem.
As for your 'points'... they cry of a lack of deep understanding of both Go, and AI
1. Go pieces can be removed from the board, by capturing. Thus opening up more combinations
2. Even if it weren't possible, and a stone was plunked down each time, you'd still have (19x19)! possible moves (a lot, as stated earlier)
3. When chess pieces are removed from the board, it collapses the search tree. On a Go board, it expands it.
4. There are 4 'cells' Remember, in a Ko battle, a space can be empty, but unplayable.
5. The whole cells argument is pretty nonsensical anyway? You are basically discussing bit-depth... in which case, would a black and white face be easier for a computer to recognize than a grayscale, how about color?
6. Facial recognition really has nothing to do with Go in a practical sense. Facial recognition is categorization based on large differences. In go, you have to select the best move based on extremely small differences in extremely similiar layouts.
7. As far as the "million game database" This just will not work, as playing against a human, they'll just do a profitable, but nonsensical move. It is the same thing that happens when studying Joseki. People will know the Joseki, but without an understanding of the principles behind it, it will be useless to them as they will not be able to respond to non-standard moves (GNU Go has a Joseki database I believe).
---Lane
You need to learn more about the game, I think, before you try to explain it to others.
This isn't as much "normalization" as it is "don't take so many drugs when you're designing tables."
Anyway, the other posts concerning the search branching factor difference in the two games are right on.
Typically, there are a few hundred possible legal moves in any Go position. It is simple to write an alpha-beta search that does well in chess because of the relatively small branching factor (the free Java AI web book on my site has an example).
Really, Go is an ideal testbed for AI, but currently the best Go programs are good engineering projects, but not really good AI projects. I would consider a great Go project to include these features:
-Mark