John Fairbairn wrote:"Direction of play" cuts through that. However it also loses something. I suspect what has happened over the years is that direction of play in the west (and possibly in Japan) has been seen as a vector, i.e. it has magnitude as well as direction.
Why do you think it has come to mean that? That a direction isn't a vector is part of the meaning of the words, since a vector is direction plus magnitude. So I don't know that I'd think your choice of term was at fault.
I took a brief look, btw: and I found that Charles Matthews glossed Kajiwara as thinking of direction as a vector: https://senseis.xmp.net/?DirectionOfPlay%2FDiscussion. So perhaps this is a common misconception. But it's a weird one.
Remembering always that we are talking about very subtle (and putative) differences between possible moves - as part of the effort to grasp what AI might teach us - I think talking about direction of play as meaning development or movement or haengma or the like is on the wrong track. Pinpointing the move that follows an assessment of the direction of play (as in western current usage) is a way of adding or over-emphasising magnitude. Or, better, if we try to follow O's thinking as he doesn't mention direction of play, it is making us think about the locale of the next move. It tilts us towards the local as opposed to the whole board.
I repeat what O has said. This method of using size of moves as a measure has been incredibly useful for us. Even where AI prefers a different move it does not automatically mean that the human move is bad. The AI move might only be microscopically better. But it is precisely that smidgeon of improvement that we are trying to understand. It seems to me (and I think this is the thrust of what O is saying) is that we may need to take several large steps back in order to move that inch forward.
That, by my reckoning, includes re-assessment of direction of play. What I believe has happened is that we players (possibly pros, too) have become accustomed to treating the direction of play as a way of finding the next move (i.e. emphasising development or movement), but what that entails is two questionable things. One is viewing a stone or group of stones as having a dominant direction (which is partly why it becomes a vector), instead of remembering that that stone/group exudes power in every direction. (I have already said that its implied plurality in the Japanese original is one aspect that is being lost.) I think even Kajiwara is guilty of this. The other glitch comes about because of thinking of playing from that stone/group. We don't do this when we have thickness - we play to drive the enemy towards it. But I mentioned in another thread a recent book which tried to emphasise that even a single stone has thickness, and I think that is what is being forgotten by us but picked up (invisibly almost) by AI programs. And, as I say, we may need to change our mindset radically to find that extra inch.
To try to wrench thoughts away from the go board and all the fixed but different associations we all have with it (e.g.. development may mean different things to different people), let me transport you to a different world.
There is a good Scots word 'airt' which means direction or quarter. Rabbie Burns uses it in the following poem. (blaw = blow, bonie = bonny and lo'e [pronounced loo] = love).
Of a' the airts the wind can blaw,
I dearly like the west,
For there the bonie lassie lives,
The lassie I lo'e best:
Following the usual stereotype you might think this is about a lovelorn poet who is about to embark on a journey to the west towards his lady love. This would be an analogue of the stereotypical thinking about developing from a stone/group on the go board.
In reality Burns had moved from a barren farm to another part of the country and was tilling and renovating a new farm to bring his wife to. So the true "direction of play" here was the reverse of the stereotype. As with thickness, this has its analogue in go, apparently overlooked in the case of single stones or small groups.
Now a different usage, but still by a lovelorn Burns.
O wert thou in the cauld blast,
On yonder lea, on yonder lea,
My plaidie to the angry airt,
I'd shelter thee, I'd shelter thee;
Or did Misfortune's bitter storms
Around thee blaw, around thee blaw,
Thy bield should be my bosom,
To share it a', to share it a'.
Here he talking about using a strong position not to develop but to defend - he is saying he wants to use his plaid (tartan cloak) to shelter his love from the direction the cold and angry wind is blowing (for the rest, bield = shelter and you need to be well up on your subjunctives). I suggest this too has often overlooked analogues in go.
Let us now return to the go board and consider this position from O Meien.
I was very much taken aback to find that this very ordinary looking position has never appeared in pro play. I triple checked in amazement. Although O said nothing about why he chose it, I assume it was because he wanted a tabula rasa to make his point. Which was that a move around A is the duh move here. He was talking only about size of move, on the basis of the sort of thinking that goes "if I don't play there he will play there and that's HUGE for him." I'm sure we all recognise that approach. If we add direction of play to the mix (which he did not) and apply it in the usual way, the case for A becomes overwhelming. After all the direction of play for each Black corner group is down the right side and to let White scupper two directions at once must be suicidal, no?
O, trying to approach this from an AI perspective, suggests a different way of playing, as follows. He plays keima in the top left, allows the double extension for Black on the right, then does an AI shoulder hit at A.
He says the shoulder hit this early would not have previously occurred to pros because it allows Black B or C, both of which confirm Black's territory (and are, of course, ajikeshi). (But, trying to think like an AI, he goes on to postulate Black E now instead of B or C.)
Now what I get when I run LeelaZero is that the AI essentially agrees with his new way of thinking. The difference is that it chooses the keima at D (and not c14) as its best move, and even at this stage it rates the shoulder hit as second best. The wariuchi on the right is certainly considered but is microscopically lower (52.1% against 52.4% but these tiny edges are what we presumably need to focus on).
It might shock O but LZ barely considered his White keima, so I would infer he needs to think even more about some aspect of play in that corner. My guess is that the LZ keima protects White better from the angry airt of the directional power of Black's upper right shimari. O may also be shocked to learn that after this keima, LZ does not opt for the double extension the right side. It prefers E, though in this case the difference between E and a move in the right centre is nanoscopic rather than microscopic.
LZ, after its White keima at D, looks at a clutch of moves in the right centre and also a clutch of moves (though rated lower) in the upper left (including another early shoulder hit), but E is a singleton in that area. Possibly it sees singleton moves as more urgent, or prefers the certainty of a single choice that maybe allows a deeper search (???).
Anyway, I think direction of play (among other things) merits some re-appraisal. But, if you allow me to share an impression I often get, I can't shake the idea that, as here, suggestions for new thinking are resisted on L19 in a knee-jerk way, and I find that strange. Even if you think about something and come to the same conclusion you had before, the very act of thinking has made you stronger. And that leads to a another new idea: direction of thinking...
Now I cannot help but think of each stone as having reverse gravity, or negative gravity, like a white hole. Putting stones together increases their negative gravity (decreases their gravity). If you have groups on the board, they repulse each other so that new stones would rather be on open areas.
Here's a demonstration of a white hole at 7:00
(it is likely erroneous but logical to think of big points as deep and thick stones or groups as mountainous in this fashion).
On Go proverbs:
"A fine Gotation is a diamond in the hand of a dan of wit and a pebble in the hand of a kyu" —Joseph Raux misquoted.
I find it actually sort of interesting that my personal "policy net" (and probably that of any other mid-dan player) with no conscious reading can be more accurate in sharp tactics and life and death, or at least be competitive. Unsurprisingly, when you add in search though, the whole thing becomes incredibly strong, as the search solves precisely those tactical things that the neural net was worse at, and then the power of the neural net for open-space and overall global judgment absolutely shines.
...
Maybe two main factors contribute to competence in most single-player competitive fields of endeavour including active sports and mindsports: field-specific skill, in which humans excel pound to pound, and interdisciplinary skill, mastered by machines not just in calculation ability but emotional control Machines train their field-specific skill many times more efficiently than any human can until it surpasses any human's field-specific skill.
Go-specific skill, then, might be knowledge of go principles and shapes, and the ability and speed with which they are recoginsed. On one end we have proverbs such as 'two from one, three from two' and on the other intuitive sensitivity too difficult to describe in human language with great accuracy.
Interdisciplinary skill might include mental acuity, physical strength and fitness, factors in which machines easily outpace us. It proves useful in surpassing humans but still seems to be underestimated by many people. Ironically, if someone who only recently learned to walk with normal mental acuity and physical fitness believes her or himself to be 'stronger than they play', implying their go-specific skill supersedes their interdisciplinary skill to great degree, without extenuating circumstances it somewhat turns into a self-directed insult when the only conclusion left is that the aspects they lack in to great degree are those in a different branch of interdisciplinary skill: discipline, patience, and others related.
Last edited by Elom on Thu Aug 23, 2018 11:26 am, edited 1 time in total.
On Go proverbs:
"A fine Gotation is a diamond in the hand of a dan of wit and a pebble in the hand of a kyu" —Joseph Raux misquoted.
Well certainly the size of a move, even as estimated by Ishida Yoshio, nicknamed "The Computer", has been typically undervalued in the opening. The two moves of an enclosure together have gained 25 points plus, yet books on evaluating positions count territory of less than half that value.
It doesn't undermine the point you are making, but my memory of what Ishida mainly said is not quite that.
Well, I just mentioned Ishida in passing, maybe unfairly.
First he stressed he was talking about big points only. Then I think he said that any big point in the opening (first move in a corner or on the side, or shimari or kakari) is worth not quite 20 points, but if the move has a follow-up (or denies the opponent one) it is worth a little more, and he accordingly distinguishes Super Big Points (23-24) points, Class I (22-21 points) and Class II (20-19). If a move is worth 25 points or more it is classed as an urgent point rather than a big point.
Personally I never really understood what these numbers meant or how they were reached, but I'm pretty sure they are specifically to do with big points.
Well, he does get into middle game plays and endgame plays, as well.
It is important to note a couple of things. First, Ishida is using deiri values, so to find how much a play gains you have to divide by 2. Second, he is offering a refinement of traditional values. For instance he starts off by saying that the first move in an empty corner is worth 20 pts. That is consistent with the traditional value of a handicap stone as 10 pts. (20/2 = 10. )
What I also remember clearly some (?)40+ years later is that when I first opened his book and saw moves labelled as 20+ points I thought I had found gold in them thar hills. For me, at least, it turned out to be fool's gold.
I don't know when the book was first published. But I don't think that it was until the late 1970s that people began to realize that the traditional values were too small. I estimated the value of a handicap stone at around 14 in 1976, but I didn't publish anything. In 1977 the AGA Journal published an article based upon statistics claiming that correct komi is 7 pts., which is consistent with a value of 14 pts. for a handicap stone. That also indicates that the first move in an empty corner is worth 28 pts. in deiri values. So Ishida was on the right track, he just didn't go far enough.
The Adkins Principle: At some point, doesn't thinking have to go on?
— Winona Adkins
John Fairbairn wrote:"Direction of play" cuts through that. However it also loses something. I suspect what has happened over the years is that direction of play in the west (and possibly in Japan) has been seen as a vector, i.e. it has magnitude as well as direction.
Why do you think it has come to mean that? That a direction isn't a vector is part of the meaning of the words, since a vector is direction plus magnitude. So I don't know that I'd think your choice of term was at fault.
I took a brief look, btw: and I found that Charles Matthews glossed Kajiwara as thinking of direction as a vector: https://senseis.xmp.net/?DirectionOfPlay%2FDiscussion. So perhaps this is a common misconception. But it's a weird one.
Well, "direction" of play should (IMO, in agreement with Charles) be a vector. And that's why Kajiwara was wrong (according to today's bots). Look at it this way. Influence falls off geometrically with distance, and as a result, adjacent corners are simply too far apart for Kajiwara's conclusions. More later on this point.
The Adkins Principle: At some point, doesn't thinking have to go on?
— Winona Adkins
John Fairbairn wrote:I repeat what O has said. This method of using size of moves as a measure has been incredibly useful for us. Even where AI prefers a different move it does not automatically mean that the human move is bad. The AI move might only be microscopically better. But it is precisely that smidgeon of improvement that we are trying to understand. It seems to me (and I think this is the thrust of what O is saying) is that we may need to take several large steps back in order to move that inch forward.
Well, it seems (to me, anyway) that that smidgeon is well within the bots' margin of error. Which means that trying to understand that smidgeon is straining after gnats. Meanwhile, current bots are indicating fairly large errors, even by pro 9 dans. That's where we should focus now.
The Adkins Principle: At some point, doesn't thinking have to go on?
— Winona Adkins
Elom wrote:Now I cannot help but think of each stone as having reverse gravity, or negative gravity, like a white hole. Putting stones together increases their negative gravity (decreases their gravity). If you have groups on the board, they repulse each other so that new stones would rather be on open areas.
Here's a demonstration of a white hole at 7:00
(it is likely erroneous but logical to think of big points as deep and thick stones or groups as mountainous in this fashion).
Does your idea of gravity agree with present ideas of light and heavy? Putting stones together might make their combined gravity positive, e.g. a poorly shaped heavy group or or more negative e.g stones in a sabaki group.
I recall that Takemiya said people should make the moves they feel like playing. He had directed this comment at amateur, and thus implicitly weak, players. It seems that the zero-type AI players learn by trying things and seeing what happens. This works for them because they play many millions of games in a short time. Humans also learn by playing, without studying. Most of us might know of players who learned the rules at some demonstration, began attending local club meetings and never studied but reached SDK or even low dan kevels without any studying except playing their games. Unlike the AI that plays millions of games, these people play, perhaps, hundreds of games or maybe a few thousands, but the learning process is the same, AI or human. We more serious or studious humans stopped just playing and seeing what happens because we've incorporated what we've studied, and that narrows what we consider playing. Having a larger scale field of view would benefit us. We also have "styles of play" that limit us. Flexibility is also needed, another characteristic AI players have. I'd like to know what sort of principles there might be that the AIs also follow. Perhaps something like efficiency of moves might be one.
Let us now return to the go board and consider this position from O Meien.
I was very much taken aback to find that this very ordinary looking position has never appeared in pro play. I triple checked in amazement. Although O said nothing about why he chose it, I assume it was because he wanted a tabula rasa to make his point. Which was that a move around A is the duh move here. He was talking only about size of move, on the basis of the sort of thinking that goes "if I don't play there he will play there and that's HUGE for him." I'm sure we all recognise that approach. If we add direction of play to the mix (which he did not) and apply it in the usual way, the case for A becomes overwhelming. After all the direction of play for each Black corner group is down the right side and to let White scupper two directions at once must be suicidal, no?
O, trying to approach this from an AI perspective, suggests a different way of playing, as follows. He plays keima in the top left, allows the double extension for Black on the right, then does an AI shoulder hit at A.
He says the shoulder hit this early would not have previously occurred to pros because it allows Black B or C, both of which confirm Black's territory (and are, of course, ajikeshi). (But, trying to think like an AI, he goes on to postulate Black E now instead of B or C.)
Now what I get when I run LeelaZero is that the AI essentially agrees with his new way of thinking. The difference is that it chooses the keima at D (and not c14) as its best move, and even at this stage it rates the shoulder hit as second best. The wariuchi on the right is certainly considered but is microscopically lower (52.1% against 52.4% but these tiny edges are what we presumably need to focus on).
It might shock O but LZ barely considered his White keima, so I would infer he needs to think even more about some aspect of play in that corner. My guess is that the LZ keima protects White better from the angry airt of the directional power of Black's upper right shimari. O may also be shocked to learn that after this keima, LZ does not opt for the double extension the right side. It prefers E, though in this case the difference between E and a move in the right centre is nanoscopic rather than microscopic.
LZ, after its White keima at D, looks at a clutch of moves in the right centre and also a clutch of moves (though rated lower) in the upper left (including another early shoulder hit), but E is a singleton in that area. Possibly it sees singleton moves as more urgent, or prefers the certainty of a single choice that maybe allows a deeper search (???).
Anyway, I think direction of play (among other things) merits some re-appraisal. But, if you allow me to share an impression I often get, I can't shake the idea that, as here, suggestions for new thinking are resisted on L19 in a knee-jerk way, and I find that strange. Even if you think about something and come to the same conclusion you had before, the very act of thinking has made you stronger. And that leads to a another new idea: direction of thinking...
I ran ELF to see if it had a different opinion and it did. To attach the enclosure in the upper right corner is it first idea. The enclosure LZ suggested is barely considered (74 playouts when I stopped the analysis).
John Fairbairn wrote:Let us now return to the go board and consider this position from O Meien.
I was very much taken aback to find that this very ordinary looking position has never appeared in pro play. I triple checked in amazement. Although O said nothing about why he chose it, I assume it was because he wanted a tabula rasa to make his point. Which was that a move around A is the duh move here. He was talking only about size of move, on the basis of the sort of thinking that goes "if I don't play there he will play there and that's HUGE for him." I'm sure we all recognise that approach. If we add direction of play to the mix (which he did not) and apply it in the usual way, the case for A becomes overwhelming. After all the direction of play for each Black corner group is down the right side and to let White scupper two directions at once must be suicidal, no?
Actually, direction of play (at least for me) is what makes the right side look big. Change the directions of the two enclosures and the right side becomes so-so. (IMO.)
O, trying to approach this from an AI perspective, suggests a different way of playing, as follows. He plays keima in the top left, allows the double extension for Black on the right, then does an AI shoulder hit at A.
Pity he did not seem to try the position out on one or more of the top bots. As you point out below, F-17 looks better than C-14.
He says the shoulder hit this early would not have previously occurred to pros
Go Seigen excepted, OC.
because it allows Black B or C, both of which confirm Black's territory (and are, of course, ajikeshi). (But, trying to think like an AI, he goes on to postulate Black E now instead of B or C.)
Right.
Now what I get when I run LeelaZero is that the AI essentially agrees with his new way of thinking. The difference is that it chooses the keima at D (and not c14) as its best move, and even at this stage it rates the shoulder hit as second best. The wariuchi on the right is certainly considered but is microscopically lower (52.1% against 52.4% but these tiny edges are what we presumably need to focus on).
No, they are not. 0.3% is well within Leela Zero's margin of error. Playing around with AlphaGo Teach makes me think that its margin of error is at least 1%, even with 10,000,000 simulations. With that small a difference the wariuchi looks fine.
It might shock O but LZ barely considered his White keima, so I would infer he needs to think even more about some aspect of play in that corner. My guess is that the LZ keima protects White better from the angry airt of the directional power of Black's upper right shimari. O may also be shocked to learn that after this keima, LZ does not opt for the double extension the right side. It prefers E, though in this case the difference between E and a move in the right centre is nanoscopic rather than microscopic.
Of course, yo! Margin of error.
Anyway, I think direction of play (among other things) merits some re-appraisal.
Absolutely.
Last edited by Bill Spight on Thu Aug 23, 2018 11:16 am, edited 1 time in total.
The Adkins Principle: At some point, doesn't thinking have to go on?
— Winona Adkins
explo wrote:I ran ELF to see if it had a different opinion and it did. To attach the enclosure in the upper right corner is it first idea. The enclosure LZ suggested is barely considered (74 playouts when I stopped the analysis).
Great idea!
Just a note about the long sequence of play. That is worth something qualitatively, but each ply increases the margin of error, so it needs to be taken with a large grain of salt.
The Adkins Principle: At some point, doesn't thinking have to go on?
— Winona Adkins
explo wrote:I ran ELF to see if it had a different opinion and it did. To attach the enclosure in the upper right corner is it first idea. The enclosure LZ suggested is barely considered (74 playouts when I stopped the analysis).
Great idea!
Just a note about the long sequence of play. That is worth something qualitatively, but each ply increases the margin of error, so it needs to be taken with a large grain of salt.
Agreed. I added in case someone wondered what it had in mind. Actually, for a while, the main variation involved pushing a ladder...
Well, "direction" of play should (IMO, in agreement with Charles) be a vector.
I'm not disputing that this can be a useful way of looking at things. The questions I am raising are whether this is what the Japanese ishi no hoko means (and I think not quite, though there is some overlap) and whether either variant of DOP is in some way a useful prism for looking at AI programs.
Well, it seems (to me, anyway) that that smidgeon is well within the bots' margin of error.
I don't yet feel this point is well founded. I admit I sloppily put simple winrates but I don't have the mathematical background to express these things properly and it seems from other threads here that there is debate even among experts what winrates even mean. But what also seems clear to me is that they alone are not a measure of a moves value, and for that reason their margin of error (on its own) is largely irrelevant.
LZ, via Lizzie, actually expresses a move's evaluation in a two-dimensional way. There is winrate and a figure that seems to mean something like number of rollouts. I have no idea how important each of these factors is relative to each other but LZ seems to think rollouts is very important because it will sometimes choose a move with a low winrate but high rollouts over one with a higher winrate and low rollouts.
But on top of that there seem to me to be other important factors, such as time, i.e. the stage in the game at which the evaluation is made. So it is really a multi-dimensional evaluation. Even a multi-dimensional value can have a margin of error of course, but from the practical point of view of a bot choosing a type of move consistently, I'm not clear whether margin of error then matters so much.
There is a related point you make: that margins of error multiply as you go deeper into a search. I can "see" that but I can't relate that to the other thing I "see", which is that chess programs generally perform better the deeper they search. I have suspected from the very beginning, and still believe, that the bots out-perform humans in go mainly because they search better and so make fewer crunching mistakes (and for that reason - i.e. it's the last mistake that decides the game - all the "research" into josekis and fusekis is somewhat misguided). AlphaGo Zero seems to have upset the apple cart, in chess as well as go, but until shown otherwise I will still believe that it is ultimately just searching better (not just deeper but perhaps because it makes a better selection of candidate moves and prunes better). So if a new version of AlphaGo came along with the same policy network but had the hardware to do an even deeper search, I'd initially expect that to be even stronger - notwithstanding the multiplication of the margin of errors that it would surely still be making. Is there some way the margin of error in talking about the margin of error cancels out the original margin of error? In a vague way that seems to be why Monte Carlo search works.
If the best ending sequence is short enough (practically deterministic, aka known), Monte Carlo will find it.
If the best ending sequence is too long (practically stochastic, aka unknown) (think Igo Hatsuyoron #120 or mildly shorter ) Monte Carlo will find a suboptimal play that is sometimes difficult to refute.
I am not sure computing power will develop in a way that all go problems will become "short enough"
) 
With that small a difference the wariuchi looks fine. 
) Monte Carlo will find a suboptimal play that is sometimes difficult to refute.