# Some general questions from a new player

About joseki and using pro game databases: unless you are aware why a joseki is good and why pro players play certain move, you’re not going to be able to take advantage of your opponent when they stray apart from conventional moves.

Actually, many joseki are not even the optimal play, as we have seen since AlphaGo taught us improvements of century-old patterns. It is likely that current day AI also makes mistakes, and that there exist even better joseki out there.

And, how good a joseki is, will strongly depend on the overall position of the game. Some joseki are considered good, but also very difficult to use.

Finally, as others have said, joseki and pro game databases will only get you about 20 moves into a game that lasts 300. I’d say that most points actually get distributed in the midgame, rather than the opening. There are even people who can gain a significant advantage from being good at just endgame.

The only real mathematical approach to go strategy that I’m aware of is endgame analysis (and only the very last part of endgame). The opening, midgame and early endgame are all done more intuitively than mathematically (not that those two have to exclude each other, on the contrary, mathematics done well should be intuitive).

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Yes, possible outcomes I meant studying the game as a procedure, not while playing.

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It may need a database…but hard to not call modern AI a mathematical/programmer approach…
and it did turn out to be strongest of all. So perhaps that idea is a bit lacking

however, more important to human level play… WRT to joseki, they are just optimized corner patterns… from both players point of view. There is not like “lower right corner joseki”, because there is not a best pattern for the lower right in a vacuum. Each joseki option will accomplish something different. If they are just generically applying joseki, OK they will probably not die… I don’t know that the outcome will be so amazing or as powerful as you may be expecting if the player was not considering the preferable outcome when selecting what joseki to use.

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It’s actually not that hard. We have literally no idea how modern AI think. They learn the stuff themselves by practice. We don’t teach them strategies, we don’t tell them how to count or how to read, we just let them try and as if by magic they learn the game. If I would describe how an AI knows what to play, it is not because it has been programmed to play a certain way, but it is because of intuition gained from practice.

It’s like Gia’s comparison from before: baking bread is not much more than a chemical process, but a good baker is not a chemist. Strong AI are made with programming, but they know how to play without involving programming.

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Mmmmm, I think it is pretty easy to say there is nothing going on in the box but math and programming.

It is not thinking at all, its performing the steps and pulling data from databases.
You didn’t write the steps, and don’t know them. The steps are not straight forward or something that is going to be reduced to 10 bullet points you can study…

But there is just no way to argue it is not math and programming lol. Sorry man.

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I’m not saying it’s not based upon math and programming, I’m saying that building a modern AI to play Go is not a mathematical / programmer approach to playing Go. Our brains function through electrical impulses flowing between neurons, but that doesn’t make an electrician an expert in psychology (nor in programming).

There’s a difference between the two things. An AI is a computer program (duh), but the way it plays go has nothing to do with programming.

As for what I would actually consider a mathematical approach to Go, it is more along the lines of this type of thinking

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Greetings! Let me re-phrase your question in a couple of different ways that may shed some light on things.

So, given the assumptions that

1. there are many high-quality AI Go tools out there, and
2. the main priority for online Go players is to increase their rankings by any means available (even if that means cheating)

the obvious question becomes, “Well, why isn’t everyone using AI assistance and cheating all the time?”

The surprising answer - as several people have already pointed out - is that it is not as much FUN as ranking up due to your own time, effort, and skill growth.

Now, do people cheat and use AI assistance on OGS? Yes, they sometimes do - and the OGS admins do an incredible job in identifying those situations and handing out consequences as appropriate.

However, in my opinion, this seems to be the exception rather than the norm, and the main reason is that rather than playing a game and learning from it, using an AI’s moves turns the active player into a passive transcriber - reduced to doing data entry without even necessarily understanding WHY the AI’s move was better than the moves they could come up with on their own. It turns out that - for most players the priority isn’t their abstract ranking - it’s their actual skill in being able to play the game, and the joy that comes from real growth and improvement.

As a counter-point, there have been many interesting threads on the OGS forum regarding different ways to use those AI Go programs as learning tools without resorting to cheating - ways that actually increase one’s skill and understanding of the game over time:

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Cooking and especially baking are basically chemistry, but I doubt a Nobel prize winner chemist can beat a chef just by having access to every chemical reaction possible

Lets look at this…
Cooking = go
chef = human acting on intuition instead of pure science
chemist = programmer, just using base rules to produce a result without any intuition.

We did this one, the chemist (deep mind) beat the ever living hell out of the chef (Lee)
Good movie

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Programming an AI to do the thinking for you is not the same as solving a problem with a programming approach. If the AI was playing go following some (humanly interpretable) program, we would be able to understand the rules it uses to decide on moves. “Why did the AI invade the 3-3?” cannot be reduced to some rules, the only thing we can say is that somehow the neural network gave that move the highest score.

Compare it to neural networks that recognise handwriting (kind of the archetypical AI example). A programmatic approach would involve describing the structure of the shape (if it has two holes, then it’s a “B” or an “8”, if it has one hole then it is an “o”, “p”, “q”, etc. if it has no holes then it is an “x” “z” “c”, etc.) and making some stepwise heuristic of determining which symbol you’re seeing. This is not at all what neural-based AI do, though. The patterns that AI look for are very different from anything humans can work with. See for example this excerpt of a 3blue1brown video on neural networks, where he shows what a neural network actually does to recognise handwriting (the whole series is recommended, by the way). It also shows a major flaw: his neural network will recognise certain random noise as if it is clearly a certain letter. There are even ways to fool an image recognition into giving a nonsensical answer by changing just a single pixel.

If you ask the programmer to make some changes to his code, so that the AI will stop invading the 3-3, for example, then the programmer has no way to implement this: the only option is to start from scratch and give the program a penalty for playing 3-3 invasions before you start training it. If instead the AI was using a mathematical heuristic to play Go, this would not be a problem at all, since you could just change the heuristic slightly.

Buildings are made of stone, but that doesn’t make a geologist good at architecture.
Sound is just physical movement of air, but that doesn’t make a physicist a good musician.
The strongest go players are built by programmers, but that doesn’t make a programmer good at Go.

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There is also a book called “Mathematical Go”
https://senseis.xmp.net/?MathematicalGo

Very technical stuff. I own a copy, but don’t understand it.

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I’ve ordered it yesterday, together with John Conway’s “On Numbers And Games”, but it takes a few weeks to arrive…

But this is indeed how Go would be approached mathematically. Very distinct from anything any go player would use, and only useful for those who want to play the last 20 moves of the game flawlessly. For the rest of the game it has no use.

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Also useful for decorating the office space of this tireless pedant

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I fully understand your point, actually I felt just like that with modern correspondence chess, but the truth in there is that, without using and knowing how to use an engine, you will not win any games against engine equipped players.Hence my question.

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The good thing is that people who play at your rank will be about your strength, whether they use an engine or not. If they would always win, their rank would be higher, and thus you wouldn’t play them.

By this logic only high level dan players have to be afraid of people who relay moves by an engine, although there is of course ‘assistance’ with an engine, where the player only occasionally uses an engine, or only uses it to check the score / count, etc. But then, these players still play at the level of their rank, so from your perspective there should technically be no difference (except perhaps morally speaking). Same thing holds for the joseki dictionaries / waltheri.

What’s a larger problem is sandbagging: people who deflate their ranks by escaping / resigning games to get to a lower rank and beat other players. But this is something that is a lot easier to recognise, and the moderation takes care of this very well (at least in my experience, I’ve not often felt I was playing a sandbagger).

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This is one of the most important points in the thread.
If you hunt for the cheaters, you can go nuts trying to prove the cheaters.
Largely, if someone has a stable rank, reguardless if it involves unfair outside assistance, you are playing against the sum total of inputs to that account, which has still been ranked at that level.
Best to steel man opponents. Outcomes will be largely the same, only difference being your outlook at the end

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I appreciate your point and understand it, but the fact I play other 25k players does not mean they are not using an engine and will not soon be way above whilst I will still be buried under, with all the other 25ks that do not use engines. If you assume these tools give you a decisive advantage, at some point you have the bottom rows, neatly stacked at the lower levels because they do not use these tools, and the other guys at the higher levels pretending they do not use them. (mind you, this reasoning is teleported from chess, I have no idea if the same principles apply to engine using players in Go, from what I’m reading it seems it does not necessarily does)

I’ll be quite honest, there is a fundamental issue of trust here from my side, in the sense that, goes without saying, my question derives from the fact that I do not trust the ‘anti-cheating mechanisms’ this type of gaming sites use, neither do I trust other players not be armed to the teeth with engines, libraries and god knows what. My question was, as I said, more to understand if my ‘toothpick’ will be enough for the battle, or if I also need some nuclear weaponry. I’m happy playing by myself, using my own knowledge but, this assume we’re all (or the vast majority) on a level playing field, according to rank of course, as I mentioned before, my experience from chess is that, if someone is armed to the teeth and you’re not, you’ll be pommelled continuously, so I decided to ask this to figure out if this was the case with go. I can see the obvious difference between games that end around 30-40 moves (in some cases, much less) and a game that can go to 100-200 moves and how that would affect the usage of electronic aides.

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The fact that our server is not suddenly filled with 9d’s since Leela and the likes have become freely available shows that it’s not how you think it is.

I’m convinced most players here are not cheating, and if they are, they do it proportionally to their level, because there hasn’t been a sudden shift in ranks.

The main reason for playing at 25k is most likely lack of experience / knowledge of the game, and not that the rest of the site uses engines.

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Personally, I don’t think you’ll gain anything by not playing your own moves and only relying on AI, libraries etc. It will get you nowhere.

Maybe some players slip through the cracks in higher ranks, but a decent good player, who became a good player by themselves, will surely rise.

I don’t understand if you mainly worry you won’t win or you won’t learn, because the nuclear option maybe will speed up the first a bit, but the second will be out the window.

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In that sense , my worry is that I could end-up drawing the wrong conclusions from my defeats. I could conclude ‘well, it does not matter how hard I try, I’m still losing’, when the answer was ‘actually, you’re losing because you’re using your (little) knowledge against someone that is suplementing his (little) knowledge with a big aid’.

Before any endeavour, it’s important to know all of the ground rules.Only then can you draw the right conclusion from your actions. As I’ve said, my view is rather tainted from other experiences, so I felt asking the question could draw some interesting answers to gauge the lay of the land, since you all know far more about this website and the playing that happens here. In that I was not dissapointed!

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Hmmm, what you’re saying is somewhat weird to me. Let me try to find common ground this way.

In go computers vastly outperform humans, just like in chess. If your opponent decides to cheat and use an engine to win against you, they’re going win. Exactly the same in chess.

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