pookpooi wrote:By the way, do you know how good Hassabis is in go? He states that he's not a strong go player, but a very strong chess player though. I'm guessing he's in single digit kyu?
When we played a series of handicap games, he got up to about 4k rather quickly. I coached him through a couple of online games. After that, I don't think he played much at all, seriously. So assume he's a mid-range club player - safest.
But he has an eye for games, and has been involved with go recently, so he might well have improved somewhat.
gowan wrote:Based on what I know about AI neural networks I doubt that this program can explain in conceptual terms why the moves it chooses are good.
Whilst being able to explain things conceptually makes a great teacher, it's not required for a bot to give useful teaching input. For example I gleaned some useful things from CrazyStone's analysis of my game here, notably some of the fighting sequences and trades I had not considered around the lower right corner from move 66. Whether I can incorporate those specific sequences and ideas into my general playing strength is less clear, but I don't think that's because the CrazyStone was unable to say "Broaden your mind and look at the bigger picture and try to consider more possibilities for trades and exchanges; is that move you think is sente really sente or can you make some exchanges first?" as I was able to create that conceptual lesson in natural language using my own intelligence applied to its analysis.
Last edited by Uberdude on Fri Jan 29, 2016 6:48 am, edited 1 time in total.
I think the question "can the bot explain" (doubt that this is possible) is partly a misunderstanding about different parts of a program.
"Can" is not the same as "does". And "provided by the same algorithm" not the same as "provided by ANY possible function".
In other words, a particular bot (currently) might simply return the next move. It DOESN'T offer a function "and explain the purpose behind that move". But this does not mean the program could not have been provided with a facility "explain the go reasons behind that move". Understand? The program might not have used those go reasons, comparing with the go reasons behind alternative moves and choosing which was the better move based upon most compelling go reasons. But that does no mean that GIVEN a move an AI could not be devised that explained "what does this move do".
To give a concrete example, take MFOG12. Its higher levels use MCTS to select the move to be made, but you can turn on "why" and using the AI which plays the lower levels, it can list the "go things" that move accomplishes << even though that AI can't evaluate which set of "go things" better than those associated with an alternative move at much better than 5-6 kyu level >> Being able to assemble a set of "go things" for each potential move is NOT the same problem as then being able to judge which set best (and so which of those alternative moves best).
So ........ to answer the initial question. A bot using a neuural net to PLAY go could be provided with a function that explained "what is that move good for" using any of a variety of techniques, and as the previous person pointed out, might be another neural net trained to THAT task.
This is from the paper. The network doesn't "explain" it's reasoning in natural language, but you can see how it valued different options. There's some interesting stuff there, I especially like the "direction of play" at the top: White split two 4-4 corners: which side should black approach from? In section F you can also see the next 26 moves AlphaGo sees as most likely.
If you had access to the engine, you could force it to play a move you considered, and see what it viewed as the most plausible continuation from there.
In some ways, I think this is actually better pedagogically. You have to tinker and analyze with the results to pull out lessons, but hard won lessons seem to stick better anyways.
pookpooi wrote:By the way, do you know how good Hassabis is in go? He states that he's not a strong go player, but a very strong chess player though. I'm guessing he's in single digit kyu?
When we played a series of handicap games, he got up to about 4k rather quickly. I coached him through a couple of online games. After that, I don't think he played much at all, seriously. So assume he's a mid-range club player - safest.
But he has an eye for games, and has been involved with go recently, so he might well have improved somewhat.
I just watch he give an interview with korean press and he said that he himself is 1 dan!
pookpooi wrote:By the way, do you know how good Hassabis is in go? He states that he's not a strong go player, but a very strong chess player though. I'm guessing he's in single digit kyu?
When we played a series of handicap games, he got up to about 4k rather quickly. I coached him through a couple of online games. After that, I don't think he played much at all, seriously. So assume he's a mid-range club player - safest.
But he has an eye for games, and has been involved with go recently, so he might well have improved somewhat.
I just watch he give an interview with korean press and he said that he himself is 1 dan!
Fair enough: does destroy my story that out of my five "serious" pupils he was the only kyu player.
Darsey wrote:What AI is for sale to play against it? I think that we can play against it to train. I can win GNU 3.8
SL has a list of go-playing software. It might be a bit outdated at places, but it's still a good starting point. You can find some discussion of specific products here in the Computer Go subforum.
