We could play with very slow time settings, maybe 2 or 3 hours per player. Or we could play on DGS. Players can use whatever resources they want, except for other human beings.
I’m on KGS and DGS as “OneTrue.” I’m a 2k on KGS, just registered on DGS.
Want to play a game on DGS? If I win, I’d like you to donate $20 to SIAI.
I’d be interested in a DGS game with the additional condition that each player document which computer resources they are using, either prior to the game or as soon as they start using them. I intend to use Kogo’s Joseki dictionary and the fuseki.info openings database to start with.
I’m using the same handle on KGS and DGS as on LW.
I’ll accept the bet, and request a matching donation to KIPP should I win.
I might use CGoban as well. If we both are, we might as well agree that it’s OK to use its score estimator; though I wouldn’t trust it much until the yose.
Interested onlookers, you can follow the game here. If you want to comment on the game, I would suggest a) using this comment thread and b) rot13ing your observations if they could influence play.
I’m not at all sure at the point we had reached how to estimate who’s in the lead (that can be one of the frustrating mysteries of Go). The CGoban score estimator says B+20-something (I think that overestimates the center) and the GnuGo estimator says W+15 (but doesn’t give a “visual” explanation of its guess).
First: you might be interested in the “Malkovitch” games at GoDiscussions.
LW isn’t the venue for a deeply commented game of Go, but it might be worthwhile for the players in such a game to post here with observations on where they felt the game highlighted this or that aspect of their thinking processes.
OK. I think having both players make such posts would be unnecessary clutter, so how about if we combine both into one post and the winner posts it? :-)
BTW, if you wanted to play, Blueberry, I’ll offer you the same conditions.
2k on what scale ? I was ranked as 2k on KGS before I quit—I’m not sure how well that reflects my playing ability, I was playing blitz almost exclusively.
How well does Advanced Go really work for reasonably good players (where I’m defining “reasonably good” to include 2k players, for this purpose)? What little knowledge I have of go software is well out of date, but I had the impression that unlike in chess, where computers were better than humans at tactics long before they were better overall, go programs aren’t terribly good at anything (on a full-sized board) unless one throws an outrageous amount of hardware at them.
What do you mean by “better at tactics long before they were better overall”? Getting the tactics right seems to be the point. Do you mean ‘good at seeking immediate goals but having a relatively poor lookup mechanism for evaluating possible future board positions’? Equivalently ‘Better at thinking n moves ahead but worse at guessing how good the n configurations will end up at n+5’.
Yes, that’s the kind of thing I mean, though perhaps for larger values of 5. It is customary for chess players to distinguish between tactics (stuff you can work out by searching) and strategy (stuff you can’t, where you play according to general principles / feel / high-level anticipation of what sort of thing will be happening several moves down the line).
Of course in the limit of outrageously effective searching strategy gets absorbed into tactics, but even in chess no player (human or computer) can look that far ahead. And in the not-exactly-limit of merely very effective searching, you can afford to be not quite so good at strategy if you can stomp your opponent tactically. This is generally how computers win.
The fact that computers and humans have distinctly different skill profiles is what makes “advanced chess” interesting: a hybrid with the strategic understanding of a good human player and the tactical monstrosity of a good computer player is very strong indeed.
(Having said which, I believe there’s some evidence that even a not-all-that-good human player armed with multiple computers running different programs can be scarily effective too.)
(Having said which, I believe there’s some evidence that even a not-all-that-good human player armed with multiple computers running different programs can be scarily effective too.)
If you’re thinking about the same thing I am, the player was “not-all-that-good” at chess, but knew a lot about chess programs and their different relative weaknesses and strengths.
Hypothetically, I wonder if that approach could be constructively imitated by a computer. A meta-chess program, dividing it’s computational resources between several subprograms, and combining their input to play better than the subprograms would if they had the full computational resources.
I think we are indeed thinking of the same instance. And yes, it would be interesting to try getting a computer to play that way.
Here’s a nice exploitation of a similar idea: The Fastest and Shortest Algorithm for All Well-Defined Problems; see also the discussion at Hacker News, where in particular you might want to read the comment from me that explains roughly what’s going on and the comment from Eliezer that explains one way in which Hutter’s description of his algorithm claims more than it really delivers. None the less, it’s a very neat idea.
So the actual computer Go program isn’t the advantage then: the advantage comes from having paper and pen, or a sample board, to try out different sequences? This strikes me as a little different in spirit from Advanced Chess, where the computer actually is a really good player. It’s more like Postal Chess.
I’d play Advanced Go with you. I’m a frustrated 2k in regular Go—frustrated because I’ve been stuck at 2k for a couple years.
I’d love to play with either of you, though I’d need nine stones to have a chance. I’m somewhere around 10-15k and I usually play on IGS.
The “Advanced” version sounds interesting, how in practice would you suggest implementing that for Go ?
We could play with very slow time settings, maybe 2 or 3 hours per player. Or we could play on DGS. Players can use whatever resources they want, except for other human beings.
I’m on KGS and DGS as “OneTrue.” I’m a 2k on KGS, just registered on DGS.
Want to play a game on DGS? If I win, I’d like you to donate $20 to SIAI.
I’d be interested in a DGS game with the additional condition that each player document which computer resources they are using, either prior to the game or as soon as they start using them. I intend to use Kogo’s Joseki dictionary and the fuseki.info openings database to start with.
I’m using the same handle on KGS and DGS as on LW.
I’ll accept the bet, and request a matching donation to KIPP should I win.
OK. I’m planning to use CGoban3 as my SGF editor, and Kogo’s and MasterGo for openings.
I’m sending you an invitation on DGS now. If you don’t like the settings, you can reject the invitation and send me a different one.
Looks like you got Black. Onegaishimasu !
I might use CGoban as well. If we both are, we might as well agree that it’s OK to use its score estimator; though I wouldn’t trust it much until the yose.
Interested onlookers, you can follow the game here. If you want to comment on the game, I would suggest a) using this comment thread and b) rot13ing your observations if they could influence play.
Hey, can you guys offer the game replay for viewing? That would be sweet!
And White wins… on time. :-/
Thanks for the game, it was interesting.
I’m not at all sure at the point we had reached how to estimate who’s in the lead (that can be one of the frustrating mysteries of Go). The CGoban score estimator says B+20-something (I think that overestimates the center) and the GnuGo estimator says W+15 (but doesn’t give a “visual” explanation of its guess).
Thanks for the game. In accordance with our bet, I’ll be donating $20 to KIPP.
Would you be willing to write up comments on your moves and how you used the other resources, and make a post of them?
First: you might be interested in the “Malkovitch” games at GoDiscussions.
LW isn’t the venue for a deeply commented game of Go, but it might be worthwhile for the players in such a game to post here with observations on where they felt the game highlighted this or that aspect of their thinking processes.
OK. I think having both players make such posts would be unnecessary clutter, so how about if we combine both into one post and the winner posts it? :-)
BTW, if you wanted to play, Blueberry, I’ll offer you the same conditions.
2k on what scale ? I was ranked as 2k on KGS before I quit—I’m not sure how well that reflects my playing ability, I was playing blitz almost exclusively.
Are you on KGS ?
How well does Advanced Go really work for reasonably good players (where I’m defining “reasonably good” to include 2k players, for this purpose)? What little knowledge I have of go software is well out of date, but I had the impression that unlike in chess, where computers were better than humans at tactics long before they were better overall, go programs aren’t terribly good at anything (on a full-sized board) unless one throws an outrageous amount of hardware at them.
What do you mean by “better at tactics long before they were better overall”? Getting the tactics right seems to be the point. Do you mean ‘good at seeking immediate goals but having a relatively poor lookup mechanism for evaluating possible future board positions’? Equivalently ‘Better at thinking n moves ahead but worse at guessing how good the n configurations will end up at n+5’.
Yes, that’s the kind of thing I mean, though perhaps for larger values of 5. It is customary for chess players to distinguish between tactics (stuff you can work out by searching) and strategy (stuff you can’t, where you play according to general principles / feel / high-level anticipation of what sort of thing will be happening several moves down the line).
Of course in the limit of outrageously effective searching strategy gets absorbed into tactics, but even in chess no player (human or computer) can look that far ahead. And in the not-exactly-limit of merely very effective searching, you can afford to be not quite so good at strategy if you can stomp your opponent tactically. This is generally how computers win.
The fact that computers and humans have distinctly different skill profiles is what makes “advanced chess” interesting: a hybrid with the strategic understanding of a good human player and the tactical monstrosity of a good computer player is very strong indeed.
(Having said which, I believe there’s some evidence that even a not-all-that-good human player armed with multiple computers running different programs can be scarily effective too.)
If you’re thinking about the same thing I am, the player was “not-all-that-good” at chess, but knew a lot about chess programs and their different relative weaknesses and strengths.
Hypothetically, I wonder if that approach could be constructively imitated by a computer. A meta-chess program, dividing it’s computational resources between several subprograms, and combining their input to play better than the subprograms would if they had the full computational resources.
I think we are indeed thinking of the same instance. And yes, it would be interesting to try getting a computer to play that way.
Here’s a nice exploitation of a similar idea: The Fastest and Shortest Algorithm for All Well-Defined Problems; see also the discussion at Hacker News, where in particular you might want to read the comment from me that explains roughly what’s going on and the comment from Eliezer that explains one way in which Hutter’s description of his algorithm claims more than it really delivers. None the less, it’s a very neat idea.
Since you’re above the level of any commercial Go program, why would Advanced Go be any different than regular Go?
You would never get ladders wrong. You would count yose plays accurately.
So the actual computer Go program isn’t the advantage then: the advantage comes from having paper and pen, or a sample board, to try out different sequences? This strikes me as a little different in spirit from Advanced Chess, where the computer actually is a really good player. It’s more like Postal Chess.
Having a joseki database would make a difference.
Then would a book on joseki, or other Go books, be allowed? I think I’d prefer them (or access to Sensei’s Library) to a computer program.