61–70 of 134 posts
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> You can inflate the game tree complexity just by switching from single-precision to double-precision, but that doesn't really make the game any harder. I think that absolutely makes the game significantly harder, just like playing Go on a smaller board is easier than Go on a larger board.
Hmm, would you say that poker is harder if you can raise from $10 to $50.00001 instead of $50?
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> Who is playing the 2100 master? Crazy Stone computer Go program.
Crazy Stone the Go computer program is playing a human chess player with a 2100 ranking?
Having said that I suspect there are problems with the two bishops and the 2100 Elo. Reading other posts, maybe it is 2 pawns or so and maybe 2600 Elo.
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True I edited it down to just bishops. And KGS is very inflated, a 6d on KGS vs. a 6d international professional wouldn't be contest. The normal conversion I hear is a 3d on KGS is around a 1k on Eastern Servers. Or that's my experience for people who play on KGS and eastern servers. I'm a 4k on KGS, but I know my knowledge is a bit amateur or a South Korean 4k.
Two bishops is still too much. An above average amateur chess player around ELO 2000 should regularly beat the world champion with two extra bishops.
I think a more accurate analogy would be playing a game of chess without a pawn, or two, maybe, but the game is so heavily based on opening lines that some might argue if you have a pawn handicap, it shouldn't be called chess.
Combinatorically, Go is considered pretty much the most complex game in existence, and computer go programs have been historically weak, so this seems to be quite an achievement (despite that it was against 4-stone-handicapped master passed his prime). One thing I wonder, though, if computers ever catch up to humans at Go, could we simply expand the board size a few spaces, thus dramatically increasing the problem sp…
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Two bishops is still too much. An above average amateur chess player around ELO 2000 should regularly beat the world champion with two extra bishops.
More often than not, a loss of a single piece in chess results in resignation. You have to make a serious blunder to lose a game when you're ahead by one piece. I think a more accurate analogy would be playing a game of chess without a pawn, or two, maybe, but the game is so heavily based on opening lines that some might argue if you have a pawn handicap, it shouldn't be called chess.
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Crazy Stone the Go computer program is playing a human chess player with a 2100 ranking?
No some chess program that is at good as chess as Crazy Stone is at go. This is actually a perfectly reasonable way of framing a discussion. Chess programs are stronger than the best Chess players, Go programs are weaker than the best go players, discuss. Having said that I suspect there are problems with the two bishops and the 2100 Elo. Reading other posts, maybe it is 2 pawns or so and maybe 2600 Elo.
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There are plenty of deterministic games more complex than Go, even turn-based ones. But Go is still a clear outlier due to its age and the simplicity of its rules - it's completely obvious how to enumerate the game tree. Things like a real-time strategy game aren't really a fair comparison, since they are designed to approximate a continuous game space-time as opposed to the discrete board and moves of Go. You can in…
> You can inflate the game tree complexity just by switching from single-precision to double-precision, but that doesn't really make the game any harder. I think that absolutely makes the game significantly harder, just like playing Go on a smaller board is easier than Go on a larger board.
Combinatorically, Go is considered pretty much the most complex game in existence, and computer go programs have been historically weak, so this seems to be quite an achievement (despite that it was against 4-stone-handicapped master passed his prime). One thing I wonder, though, if computers ever catch up to humans at Go, could we simply expand the board size a few spaces, thus dramatically increasing the problem sp…
Yeah. If the computer uses mostly brute force, then making the board bigger would again tilt the balance in favor of human players.
But if the program is smarter than that, well, then I don't know.
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Some go programs (e.g. Leela) support playing on large boards, up to 37x37. Algorithmically, there are two issues: Go programs use Monte Carlo estimation by doing semi-random playouts to determine the game theoretic value of a position. The longer the game is from its end, the more noise in the estimate, which worsens the playing strength. Secondly, the longer the game is from its end, the longer the computation of a…
Yeah, this is my thought. It seems, for example, that precisely calculating the optimal strategy would be quite tenable on a 9x9 board, because the problem space is so small. On a 19x19 board, the space is absolutely immense. It doesn't seem to make a huge difference with humans, though, because we are so adept at pattern-matching. So it seems like while a larger board would certainly make things more difficult to a…
PS: "Center opening results in Black taking the entire board. First play on the edge results in White taking the entire board."