To put in more westernized chess terms, this would be like beating a 2100Elo master without bishops. Yoshio is a professional and very skilled, but he hasn't won a major tourniquet since 1989. Really not an achievement, its nice to see Computer Go advancing.
A 4 stone handicap between master's is massive. The difference between a 9d (dan) and 1d isn't actually 8 stones. With an 8 stone handicap a 1d will play a 9d off the board (provided both are profession dans not amateur). Source http://www.amazon.com/Kages-Secret-Chronicles-Handicap-Go/dp...
Generally I would say that this should put it around US 2-4d (for US Go Association, or KGS online). Maybe 2k-1d in professional amateur circles. I doubt it work warrant a 1-3p 'professional ranking'.
I think it's actually a pretty big deal than you're saying.
Firstly, Yoshio was one of the strongest player in the 1970s. Nowadays, despite not being as strong as he was, I wouldn't say he's equivalent to 2100Elo master. If you assume that the top player is 2800, a +700 difference mean something like .9999 probability for the top player to win against Yoshio (which practically means always). I doubt that would be the case. It's more likely that a winrate from .66 to ~.85 to be more appropriate. In other word, Yoshio would be ~2600ish ELO. That would still be an underestimate of Yoshio's strength imo.
Professional dan denotes past achievements, not playing strength. Young 1p is actually more likely to be about half a stone to a stone stronger than some older pros.
It's fairly hard to quantify how strong 9d KGS or AGA are, since there are too fews of them. But if 9d KGS is ~1 stones weaker than the pro, add on 3 more stones and Crazy Stone would be ~ 5d-6d KGS, which would be 95-98% percentile or more! That would make the computer about ~2100-2300 Elo for chess. Correct me if I'm wrong, but 10 years ago, no go program would have even come close to a mid rank kyu players.
Sorry, I know that the ranges given in the post are quite broad and might look silly, it's just hard to make any direct comparison between the system
I think .66 is substantially too low. Iyama Yuta is well over 50% against any professional in Japan, and while Ishida is still competitive in Japan, he's not a title contender anymore. So I'd wager that Iyama is at least a 66% favorite against Ishida, and Iyama is himself not 50-50 against the absolute top players (40-60 perhaps, maybe worse).
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.
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.
My FIDE rating is slightly above 1900. I think that with 2 bishops I'll beat Magnus Carlsen easily, simply because I could sacrify one bishop for some attack and still be ahead in terms of material. But with only one bishop ahead at the start of the game, I doubt it will be enough.
Well, I could easily beat Carlsen in an endgame with one bishop and one pawn up. So if I were to start a game against him with two bishops, I could develop my pieces normally and then sacrify a bishop for a pawn to throw an attack at his king (somewhere in f7 or h7 for example). Then I'll have the initiative and still a material advantage, so what could he do? I know I am not so good, but I am confident I am not gonna fall into cheap tricks.
Also, I think some part of the difference in strength between Carlsen and I lies in his massive knowledge of the openings, which will be gone if I start the game with a two bishops handicap.
2 bishops is IIRC about 700 ELO-equivalent, so this looks like a good estimate to me. (That said, 700 ELO difference is >99% winning rate, so we're in outlier territory, and as said in the other post, that would prevent me from taking bets :)
You would lose a longer match. (You're the second player posting here who seems to drastically underestimate the effect of the ELO difference. That said, 900 ELO difference is so far out on the Bell curve that I wouldn't want to take bets on this one.)
A bishop in chess is massive. I am decent amateur (2300 ELO) and I crush the strongest computers in blitz (which are way stronger than the strongest humans) with bishop odds and it's not even interesting. 4 stones is more like a pawn, massive at professional level, not much in pro vs amateur duels.
While playing vs Houdini I managed only few draws (and I lose like 95% of the time) with 2 pawns odds as well (and those were 2 pawns of my choosing, not random ones). There is huge difference between a bishop and two pawns.
I am decent amateur (2300 ELO) and I crush the strongest computers in blitz (which are way stronger than the strongest humans) with bishop odds and it's not even interesting.
Either your rating is wrong, your are not actually playing the strongest computers, you're arguing from a too small sample size, or your definition of "crush" means "I win half of the games but those that I do win I do so convincingly".
4 stones is more like a pawn
This is completely and utterly wrong. The winning odds of having a 4 stone headstart are an order of magnitude higher than those of being up a pawn.
There is huge difference between a bishop and two pawns.
Yes. About 150 ELO - equivalent. More than being another pawn up.
Do you have anything to back those claims ?
I mean I am at least decently strong chess player and I played tons of games vs Houdini 3 and 4 on modern i7 quad and as you can see at least one other person did as well.
>>Yes. About 150 ELO - equivalent. More than being another pawn up.
You can't quantify it like that. Strong chess player is going to win with bishop odds vs any entity on the other side: 2500GM, elite GM or Houdini on 32 cores. It's just a win starting from certain level and "150ELO" doesn't convey it. On the other hand there are a lot of entities which would beat me (and even some stronger players) with 2 or 3 pawn odds.
ELO, Material Difference and Winning percentage are directly correlated.
You can't quantify it like that
Of course you can. A material advantage increases the average winning probability, and does so in a way that corresponds reasonably close to the ELO formulas. No more and no less.
Strong chess player is going to win with bishop odds vs any entity on the other side: 2500GM, elite GM or Houdini on 32 cores. It's just a win starting from certain level and "150ELO" doesn't convey it.
You have no argument to support this, and there's evidence to the contrary. (See the above study). "Strong chess player" is totally meaningless, ELO is a relative scale. A 2500 player loses just as hard against a 2850 one as a 1600 does to an 1950. That's the definition of ELO.
I'm sorry but you're just not going to beat Magnus Carlsen in a long match even if he gives you bishop odds. That's exactly what him being 2880 ELO means. You would beat Karpov (!) though.
gcp, I am yet another 2350 Fide player who would take Bishop odds against Magnus any day of the week despite the 500 point difference.
The main point is that Bishop odds are different from 3 pawn odds. It tilts the game too much in the favor of the odds taker taking away most of the advantages(positional considerations, openings, etc) that a 2850 player enjoys over a 2350 player.
What happens playing against a strong computer given a bishop odds, is that computer will slowly succumb to the negative eval.
Instead a better strategy for a computer would be to try something very speculative like in old Tarrasch games with odds against amateurs.
That is computer should be on the lookout for eval -20.00 with perfect play by opponent(me) but possibility of 0.00 or even +10 when I make a wrong move. That is computer would have to try hard to create high volatility situations and hope that the 2350 player would misplay them.
I suppose that Magnus would try something similar(especially given his penchant for grinding).
Where are you getting this material advantage / ELO handicap ratio?
At any rate I'm also a decent amateur (2350 ELO) and it's absolutely unsurprising that a (2200+) player easily beats very strong computers with bishop odds.
I pointed some public research putting 1 pawn = 100 ELO advantage above. I used a different technique that didn't try to search for quiet positions, but calculated the ELO value of positional and material factors directly, and included human games as well. The mathematics to do so are (appropriately enough!) in a research paper from the Crazy Stone author.
What are you basing this on? It seems wrong both in terms of the size of the handicap and the strength of Ishida.
Ishida first: while he is certainly not top 100 in the world anymore, he is quite probably top 1000 (there are something like 1500 professionals out there, and he is probably above average for Japanese professionals, maybe above average for all the countries (see https://www.google.com/search?q=yoshio+site%3Ahttp%3A%2F%2Fi...). So he's closer to a grandmaster than a master. And in any case, other professionals have lost at four stones (see http://www.computer-go.info/h-c/index.html).
Second, regarding the handicap: I am not knowledge enough about chess to say, but it sounds high. In Go, I have beaten players who officially should give me three stones (though as you approach professional strength, it is true that players would be better at preserving that advantage and converting it into a win). I'd estimate the handicap as somewhere between 400 and 600 GoR points (which are similar in spirit to ELO ratings--http://senseis.xmp.net/?EGFRatingSystem). It is worth noting that the best European players take two to three stones from strong Asian professionals.
On March 21, 2014, Crazy Stone just beat another 9-dan professional with 4 stone handicap. The 9-dan professional, Yoda Norimoto, was among the top Go players in Japan just 5-8 years ago. He was a runners-up to several pro titles in Japan as late as 2006-2009 and was the holder of a major title (Gosei) in 2005.
This is a huge achievement. I'm an amature 5-dan (aga) and I would not bet on myself against a 9d pro with a four stone handicap. It's amazing how far computer go has come in the last few years.
> To put in more westernized chess terms, this would be like beating a
> 2100 Elo master without bishops.
This sentence is not helpful. A handicap is useless without a basic idea of the skill level of both opponents. Who is playing the 2100 master? My mom who has no chess knowledge, the casual player who knows how the pieces move but has never devoted anytime to study, or someone ranked 1500?
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.
It's a common refrain that while computing has conquered Chess, it has failed miserably (to date) with Go. The article is suggesting this is changing, valaraucal is disputing the premise of the article, that's all.
Whereas the best chess engine is better than the best human, the best go engine can only beat a weak player with a big handicap. That's all valaraucal was trying to say.
I'm a chess expert but not a go expert - I don't know if valaraucal's right - but I suspect he is overstating both the weakness of the player and the size of the handicap.
Worrying about cores etc is overthinking it, they don't make that much difference (it's not a linear problem). Houdini is much stronger (or at least has a much higher rating) than Magnus Carlsen, even on a commodity laptop.
Incidentally, if you build a chess engine from scratch, it will take a bit of effort to get an engine that can beat a 2100 player with a 2 bishop handicap. I am about 2000, I spent a couple of weeks building a toy engine (available on triplehappy.com, my website). It is rated about 1500, but it will still beat me if I don't pay attention to the tactics. Illustrative of the fact that human ratings and machine ratings are not directly comparable. To get that far I had to give it some chess knowledge and some tactical ability. When you first get a chess engine playing legal chess it is going to be lamentably weak (less than 1000).
I think I was too focused on the specifics of the analogy to realize it was a general statement. Thank you for clearing that up for me.
I did not mean to delete the comment you replied to. I have included it below:
It is terribly confusing analogy for me. Initially I thought the computer engine analogy was what was intended. But then I started thinking about someone rated 2100, down two bishops playing stockfish on a decent box with 3-4-5 EGTBs and a two bishop advantage. That seemed like a no brainer so I moved on to crafty, and then GNU chess and then what? I realized that I could not think of an engine that would consider a win with two bishops an accomplishment. As far as "maybe 2600 is a better target" goes you have to go all the way down to #88 on the CCRL in order to get to 2600.[^1] That is with even material and definitely not using 64 cores (the CCRL uses a AMD X2 4600+ at 2.4GHz benchmark).
I am sorry but thinking about a chess engine running on 64 cores with a two bishop advantage against a 2100 rated human is not reasonable. If I knew nothing about computers and Go I could reasonably read the 2-bishops/2100-ELO analogy and conclude that CrazyStone was laughable. I do not know much about computers and Go but I do know enough that I do not consider CrazyStone's performance laughable.
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 space and setting computers back a while? I guess that would depend on what kind of techniques were being used by the computers to solve the games.
I remember watching a game around 15 years ago, Go professional (I forget who) vs a highly-ranked computer program.
The computer got a 27 stone handicap, and the pro still won by more than 361 stones. Both of those numbers are crazy.
The fact that computer programs are getting competitive is pretty awesome. 15 year ago, I wasn't sure they'd ever beat a competent human. But now I anticipate that 15 years from now (if not sooner) they'll be better than pretty much everyone.
In 1997, Janice Kim (1p) gave HandTalk a 25-stone handicap: she won.[0]
In 2006, Crazy Stone ran on a 4 x 2-core CPU at 2.2 GHz and won gold in a tournament.[1] In 2013, the author purchased a 4 x 16-core CPU at 2.8 GHz for tournament play.[2] I would imagine that that was the hardware used for this game.
For such a slow machine the Monte Carlo method has proved devastating.[3] Consider that the the author's computer can reach 332.8 GFLOPs per 2P node[4] and the slowest supercomputer in the world's Top 500 list can reach 236,300 GFLOPs,[5] which is ~710 times faster. The Tianhe-2, for giggles, can peak at 54,902,000 GFLOPs, or ~164,970 times faster.
In theory, the Tianhe-2 could demolish a 9p, today. If Moore's Law holds out,[6][7][8] Crazy Stone will likely reach 9p in under 7 years, by virtue of hardware improvements alone. Were IBM to dedicate resources to Computer Go, a machine would be awarded a 9p rank in as few as 3 years.
Current Monte Carlo programs have major problems taking advantage of increased processing power, so your major assumption is flawed. I don't have a citation at hand, but there has been discussion of this on the computer go mailing list.
It's not out of the question that the engines could be tweaked to improve their performance more with better/more hardware, but right now, they have disappointing results.
"Fortunately, MCTS lends itself much more easily to parallelization" and "Although MCTS can benefit from parallel implementation, this benefit is not always as large as might be hoped" as no game-tree is constructed.[3]
I think the assumption holds: we won't have to wait 15 years; in ~7 years (or fewer) we will have 9p Computer Go players.
I don't have a citation at hand, but there has been discussion of this on the computer go mailing list.
You should post it. I suspect you misunderstood. Additional computing power doesn't help some problematic situations, but the overall strength still goes up nicely.
There are also some problems with parallel scaling not actually improving raw performance, but this is equivalent to the speed not actually going up.
Unfortunately, I can't seem to find it. I found other people on go forums saying that Remi Coulom might have said it, but not a citation.
Also, just to be clear, the claim that I'm considering is that around 4-6 dan KGS, you start getting markedly lower payoff in Go strength for increasing the number of playouts. The big concern seems to be capturing races.
> Combinatorically, Go is considered pretty much the most complex game in existence
Is that considering "game" to include only traditional turn-based board games? Presumably it would be trivial to make a video game that's vastly more complex (at least in terms of tree or state space complexity) than Go. Any real-time strategy game should quality.
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 inflate the game tree complexity just by switching from single-precision to double-precision, but that doesn't really make the game any harder.
> 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.
Only if you're brute-forcing the game. Something like smaller time steps and more precise positioning for a RTS will usually only slightly alter the optimal strategies, rather than change them to be unrecognizable, because the size of units and buildings and obstacles won't have changed so things like route finding will be basically unchanged in result and execution time. Almost everything being optimized would be locally convex at the scale of the new degrees of precision, so nothing would get exponentially harder.
In some cases I think you're right, but depending on the game I could see there being potential emergent chaos from even the slightest variations in positioning.
But Go can still be surprisingly hard on tiny board sizes.
There are, for instance, 386,356,909,593 possible 2x2 games.
(under the positional superko rule which says you cannot repeat any earlier position.)
How is this possible? Every game that I can imagine on a 2x2 board ends in about 5 or 6 moves. It seems there'd be 4 x 3 x 2 choices for the first 3 moves. Then the fourth move would capture two pieces, leaving two spaces open, so up to 48. I don't think I quite have the whole picture, but either way I can't possibly fathom how it could reach a number like you've given. What's the source of that?
The longest 2x2 game possible seems to be 46 [1].
I can't find the source for the number given by tromp either. But considering that log_2(386,356,909,593) = ~ 38 and log_3(386,356,909,593) = ~24. If the board can have a branching factor of 2.5 on average for a game length of 30 moves, the number seems reasonable. There are 81 possible states (counting illegal states), and seems to be about 50 legal states. And I'd imagine any given state on a 2x2 board would easily have more than 2 possible moves :-).
This depends on whether the game outcomes tend to vary smoothly with each step, or not. If you have a computer play computer ping (which will be smooth), then increasing precision has minimal effect.
Are top RTS games like Starcraft hard for AI? I know the default AI isn't strong, but is Starcraft in theory difficult to trounce humans? I spoke to an ex-pro player and he asserted AI could never get close, but I don't see why. It seems like being able to do precise calculations and a near infinite APM could be a significant advantage.
What makes AI difficult in these games is pattern recognition of higher level strategic abstractions. A human player can recognize that placing a Go stone or a Terran command center projects some power in regions around that spot. The human can use intuitive pattern matching to assess when he has a superior force in an area and can push to a decisive tactical victory, even if the human isn't quantifying every move in precise terms. An AI must quantify every bit of power projection somehow, which becomes impossible with present computing resources in games whose possible state space quickly explodes into 10^10 or more possibilities.
It's actually a similar problem to computer vision. Identifying a battle front from the current state of a war game and recognizing the tactical possibilities is similar to edge detection in a photograph and recognizing objects. Humans do that essentially with highly parallel computations and lookups by billions of neurons. Until we get billion-core CPUs and billion-ported RAM, AIs will not have the same capability.
Source: I've done some development on AI for Civilization. It sits somewhere between Go and Starcraft in AI capabilities. Civilization is turn-based like Go, but the state space explodes far more quickly like Starcraft when you have 100 units which can each make a dozen moves in 100! different orders on a turn. (In Civ, the order on which units act each turn is extremely important, where workers lay down railroads for other units to move, or where you attack a city with artillery before the ground pounders.)
Now that I think about it, the more interesting and challenging strategic factor in Starcraft is probably the fact that it's not a perfect information game. That's probably a big part why AIs are really good at isolated parts of Starcraft (like executing build orders in the first couple minutes of the game, or micromanaging armies in controlled situations), but really bad at actually playing a normal game and winning.
> ... could we simply expand the board size a few spaces...
People occasionally experiment with other sizes, such as 21x21 boards. The size of the board has a strong impact on the nature of the game, though.
The obvious change is that larger boards take longer to complete, putting humans at a disadvantage if fatigue comes into play. Less obvious is that 21x21 changes the value of tradition strategies. It is generally considered equivalent to play for board-edge territory as for central influence on a 19x19 board, but on 21x21 playing for the easily-defended outer regions is too small. The value of the center means that it's more valuable to play for central influence instead.
To answer your question in short: it's possible, but expanding the board size could make the game unfamiliar and decrease the effective ranking of pros.
Strategic thinking. Being able to fluidly use both linear and intuitive thought processes. Being able to apply strategic concepts learned on Go (Territory vs. Influence, life-and-death, good shapes, urgency vs. big moves, move order, etc.)
Go is a game that is abstract enough, you can easily see the same kind of patterns emerging in day-to-day life. Thus, it helps hone your ability to make decisions in face of uncertainty.
For example, a classic decision: you have a startup. Google offers an acquihire deal with you. Do you take this deal and run with the money? Do you hold out for a better acquisition deal where your product might see the light of day, or do you try to realize the potential of the company on your own? This is essentially the same decision you make when you play territorial vs. influence style, that is, realizing gains now vs. potential gains later.
Each concept in Go you learn can help you be a better Go player, but the real value is in how each of those concepts help you make decisions in your life.
You might use a computer to help you analyze things, but ultimately, the entity making the decisions for your life is you, not the computer.
I really appreciate that you put that in context -- i.e. the position of that result in regards to AI history.
“4-stone handicap” can seem odd or artificial to non-Go players, but it is a classic way of balancing a game between players with known different levels: because of the complexity of the game, mastery expands wide, and it is rare to find a player exactly at one’s level. The gameplay changes a bit when starting at an advantage, but not significantly. For PR reasons, AI advances are usually measured with matches against star players; that handicap tradition allows AI advances to be measured more finely -- and I guess have a count-down, more appealing that the ‘not beaten yet/OK, we are done’ dichotomy of Deep Blue vs. Kasparov.
> if computers ever catch up to humans at Go, could we simply expand the board size a few spaces, thus dramatically increasing the problem space and setting computers back a while? I guess that would depend on what kind of techniques were being used by the computers to solve the games.
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.
Interesting question. As a go lover I believe it would hinder the person more than the computer.
You wouldn't be able to expand the board, because then its no longer Go. There are three commonly used board sizes (9x9, 13x13, and 19x19). Other than that, it wouldn't be Go.
The computer would have an easier time playing with a larger board because its algorithmically making moves. The experience go player wouldn't have their experience behind them.
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 playout takes, which reduces the number of positions that can be considered in the tree search part.
So in fact, no, moving up in board size does hurt the program substantially. Experience with programs like the above shows it hurts the computer more than the human.
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 human, they wouldn't really have to make many adjustments in their fundamental strategy. On the other hand, it could dramatically weaken a computer player.
As to the other point raised, there doesn't seem to be any reason why it would suddenly cease to become Go if you increase the board past 19x19. The rules of Go are independent of board size, and I'm sure it took quite a long time before the "standard sizes" of 9, 13, and 19 were fixed.
Nice! I spent a lot of free time in the late 1970s and early 1980s working on my Go playing program Honninbo Warrior (played poorly, but was the first commercial Go playing product).
The new Monte Carlo search technique (used by Crazy Stone) basically blows all previous approaches out of the water. I bought the "Championship Go" app for my android phone, it uses Monte Carlo, and plays well.
Monte Carlo for Go was known for a long time. It wasn't until someone (not-so-coincidentally, the author of Crazy Stone) figured out a way to combine it with tree search and published his research, that performance began to skyrocket.
For the benefit of readers who aren’t necessarily Go players, a four stone handicap means that black (the computer) was allowed to place four stones on the board before white (Ishida) made any moves. This may sound like a lot but, while it is a significant handicap, it’s not really as big as it sounds.
In my estimation (I play go), beating Ishida Yoshio at 4 stones in a non-simul game [1] probably requires a player that's at least 4 dan amateur.
[1] Professionals usually play amateurs simultaneous games. That is, 1 vs. many. The quality of play improves dramatically if they are playing a single game. In this case, a single game Ishida probably wanted to win.
yeah; there are some people in the comments suggesting that that Ishida might not be playing at the level of a top 9p right now, but this is still pretty significant and a very impressive feat.
Probably accurate for active professionals in the big three countries, and probably a bit generous. I doubt there are many professionals, if any, who need three stones against the best. In fact, top western amateurs might be competitive on three stones. There has been some compression of professional strength in the past 50 years, so there may be some older professionals who need that much. Additionally, there are players with professional ranks who no longer compete, or only compete in Western tournaments. They may need three stones.
Would it be accurate to say those 4 stones are about equivalent to one pawn in chess?
As a back-of-the-envelope calculation, one pawn is 1/43 of your starting material in chess if the king is included as a four-point fighting piece. Four stones in Go comes to 1/45 of your expected endgame material as half of a 19x19 board.
It's hard to make a comparison like that because Go and Chess operate on fundamentally different models. Chess is about capturing a specific piece and putting your opponent in a position where they have no options but to lose; to that end, it's a war of attrition where players slowly lose resources until the game is over (note that I do not play chess at any significant level).
In contrast, Go is about capturing territory by fencing it in. Placing four stones on the board is like placing four free fenceposts; you can't really call it a tangible resource like a pawn, but it gives you more of a structure and gives you some influence over the rest of the board.
It's possible to remove resources from your opponent in go, since you can surround pieces and capture them. But it's not really an attrition thing like in chess; it's more about territory and control.
Trying to make it a numbers game and saying "four stones is 1/45 of your expected endgame material" isn't really relevant to go, because the position of the stones matters so much more than the number. If you have four more pawns than your opponent in a game of chess, that's pretty clearly an advantage; if you have four stones in a totally useless area of the board, or four stones in a really useless configuration, then they're not helpful at all.
It's hard to make a comparison like that because Go and Chess operate on fundamentally different models
It is very easy. The nature of the game is completely irrelevant. The question is what expectation of winning rate a 4 stone advantage gives to a Go player. For middle ranks, one stone is about 100 ELO-equivalent, or 64% winning rate. (I think it's closer at top dan ranks, would have to look up the statistics). 4 Stones is about 92% chance of winning between equal players.
The equivalent in chess is slightly more than 4 pawns advantage, or about a minor piece.
I've read four different versions of the comparison you're describing as "very easy" (four pieces, four pawns, two bishops, a minor piece), so you'll forgive me if I don't find your statement very convincing given the lack of consensus?
My limited understanding of go is that the stone placement confers position and tempo, too, which would be undercounted looking at it purely from points.
Points (which are a game specific metric) have absolutely no relation to anything I posted. I didn't even mention them at all! It looks purely at game outcomes given the initial starting conditions.
Yes, you've got the right answer. Forget material and point comparisons which don't really port between the games. The winning percentage conferred by the handicap is what matters.
Four stones in Go sounds like a lot less than four pawns in chess, but if that's what the math says by each resulting in the same winning percentage, then the equivalency is true.
I'm around 2000 ELO in chess and I'd win every single game vs anyone with 4 pawns or a minor piece handicap. Being a single pawn up is usually decisive in chess. Having said that, this whole discussion is pointless, no one ever gives handicaps in chess, because it completely messes up the initial position. Even lacking one or two pawns at start will make it extremely hard to establish any kind of central presence.
I'm around 2000 ELO in chess and I'd win every single game vs anyone with 4 pawns or a minor piece handicap.
You'd only break even starting from opponents at around 2400 ELO, and would start losing about 2 out of 3 games when facing a top rank grandmaster.
Being a single pawn up is usually decisive in chess.
It only gives you slighly less than a 66% chance of winning (a bit more close to the endgame).
There's no point in arguing from your personal beliefs here. You're vastly and utterly overconfident in your own ability. The definition of the rating system and a few million games of evidence are against you.
More than a pawn: I think "two bishops" was about right.
The value of each stone (as an ability to stake out territory -- sometimes called the "temperature of the board" in game theory) decreases as the game goes on. A stone in each corner is huge, probably worth about 80pts of potential territory. In the middle game, the temperature might drop from 20pts to 10pts per move. So your averaging method doesn't quite work. :)
I have played (in the 1970s) both the Women's World Champion and the National champion of South Korea - I am not going to admit how many stones they gave me and they still won :-)
Four stones is sort of like giving a child a knight off the board starting advantage in chess.
BTW, my older brother taught me Go when I was eight. We played fairly equally for many years, then suddenly within a one year period I was able to give him nine stones, a handicap I have now been giving him for decades. Not saying I am good, just that my brother is a bad Go player :-)
That's still significant progress in the past five years. 2009 was the first time AIs were able to reach dan level ranks on a 19x19 board. Crazy Stone is approximately 6 dan now.
No, but it's still spectacular. Not so long ago, I could defeat the strongest go computers. I have no chance in hell with 4 stones against a professional, or even against an amateur dan player.
www.gokgs.com is the server that's probably biggest in the English speaking world. The desktop client is Java based, there is an Android client, and we're waiting for an HTML client (it's in closed Alpha). There are several other servers that cater more to Asian players, but you can certainly play on them.
There is also online-go.com, which is web-based. It has real-time games, but the majority of games on the server are correspondance.
Resources: senseis.xmp.net (an old wiki that has lots of content, but few active contributors), and lifein19x19.com/forum, a forum dedicated to Go.
I didn't know about the KGS HTML client. Either I should hurry up with my side-project or abandon it, as that's exactly what I'm building (but obviously without the already established KGS user base).
There's also http://www.dragongoserver.net/ for those who prefer "mail time" games, i.e. ones in the order of 1 day per move, obviously asynchronous. Pretty neat if you find it hard to carve a continuous hour for a synchronous game.
On another semi-unrelated note, if you ever want to play teaching games with friends you try out this Meteor-based webapp I made. It doesn't enforce any rules, but it does show all piece movements in realtime as you drag them around, so it's a bit more like playing in person. It should be easy to run locally or on your own free Meteor instance. http://github.com/muraiki/senseinogoban There's a demo server up but since anyone can join, don't expect your board to stay in shape. :)
Someday I'd like to make it more feature complete, such as adding accounts and multiple rooms, but since I just started a new job I won't have time for a while!
http://online-go.com is a new go server with a nice web interface. It runs acceptably well through the Android web browser if you're just looking to play games. KGS is still a better place to find games and players to talk to, though.
Since it hasn't been mentioned, Tygem is available for Windows or iPad (strange combo, I know). Not big with the English speaking crowd, but it's filled with top-notch Korean and Chinese players so it's great entertainment for dan level players.
Yellow Mountain Imports has a good looking and feeling bamboo set (bowls, board, yunzi stones) for under $100. GoGameGuru has some cheap sets too, but not with bowls. Both have a shin "kaya" set for under $200.
I went to the local go club a few times before picking up my own go equipment. I wanted to get some "hands on" feel for the board and stones, to pick the brain of people who have played longer than me on a greater variety of equipment, and to find out how genuinely terrible I am at go. I live in a town where there is a decent sized Asian market area. While some of the shops had go equipment, it was subpar and way too expensive for my blood.
The set MichaelGG is talking about is the first set that I picked up for myself. It was the centerpiece of my living room for several years, and has taken all of the abuse I can throw at it (over eager new players, drunk friends, young kids, pets, the go club) in stride.
As I was still learning and teaching the game I picked up a smaller, reversible 9x9 and 13x13 board with plastic stones, and that set never sees the light of day. It's far too light and chintzy to play on now. If you're sure you want go equipment, I would take at least a bamboo board and single convex yunzi stones. The upfront cost might seem like much, but the set from YMI will last at least a generation if not longer.
Damnit! I'd finally gotten used to the disappointment that kept coming from expecting to click through a link and read about a game but instead landing in an article about a programming language.
I can play go (I am 1kyu). The game against crazy stones is really impressive. I feel that Ishida played at his best level against crazy stones and that crazy stones would not have won if it hasn't found the marvellous move 52. In the game against zen, I feel the level was lower.
The handicap of 4 stones seems to be very accurate. This means that crazy stones has the same level than top amateur players.
Generally, in Go, fast games are an advantage for computer. I wonder what would give a slower game.
Cool. Computer go has come a long way since the days I still played regularly. Back then I could still defeat the strongest go computer. There's clearly no chance of that ever happening again.
Not confusing at all. Go laid claim to the name hundreds of years ago, and the title made it clear it was the game. If someone invented a computer language called chess and there was an article title "Houdini computer chess program defeats former world champion Garry Kasparov with knight handicap" would you expect it to be about the computer language ?
A 4 stone handicap between master's is massive. The difference between a 9d (dan) and 1d isn't actually 8 stones. With an 8 stone handicap a 1d will play a 9d off the board (provided both are profession dans not amateur). Source http://www.amazon.com/Kages-Secret-Chronicles-Handicap-Go/dp...
Generally I would say that this should put it around US 2-4d (for US Go Association, or KGS online). Maybe 2k-1d in professional amateur circles. I doubt it work warrant a 1-3p 'professional ranking'.