Alpha Go to play Ke Jie in May Go forum

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Alpha Go to play Ke Jie in May
  • David J Bush at 2017-04-13

    https://arstechnica.com/information-technology/2017/04/deepm...

    It’s a three game match.

    Hassabis: "Instead of diminishing the game, as some feared, artificial intelligence has actually made human players stronger and more creative. It’s humbling to see how pros and amateurs alike, who have pored over every detail of AlphaGo’s innovative game play, have actually learned new knowledge and strategies about perhaps the most studied and contemplated game in history."

  • purgency at 2017-04-13

    I read in some leaks earlier to the official reports, that the version of AlphaGo playing will be one that has learned the game by itself from scratch without learning from human games. There is no mentioning of that in the official news, so that may not be true; but it would be interesting. At the very least I don’t expect the version that has learned from human play to lose even one of the games; after the online games that AlphaGo won 60:0 against pro players that seems unlikely, although then again those were games with like 15 seconds per move which should be a disadvantage for the human.

  • Sighris at 2017-04-26

    I’m excited! 

    http://www.usgo.org/news/2017/04/world-1-ke-jie-9p-to-take-on-alphago-in-china/ 

    From an AI perspective, it makes sense to have a decent starting point, so it makes sense to start with pro games, but OTOH, it also makes sense to remove the possibility that we humans have a blind spot (for example maybe our joseki are actually not seeing the “big picture”/whole-board and are too focused on the corners... but as far as the next match goes, It matters little to me if AlphaGo has “learned” from Pro/human games or if "the version of AlphaGo playing will be one that has learned the game by itself from scratch without learning from human games." 

  • Carroll at 2017-05-02

    Do the good players here agree with Brady Daniels analysis of two similar joseki games of AlphaGo?

    https://www.youtube.com/watch?v=6rB2cYOeppQ

    In the second game are the ko threats as big as he says?


  • lazyplayer at 2017-05-02

    Carroll, i’ve no idea how big they’re exactly, but it’s at least plausible to me that they’re big...

    Very interesting video anyway, I’ve learned something from it, even if I’ll probably never play Go... :)

  • gamesorry at 2017-05-03

    Do you mean the one around 35’15'' ? I think he’s correct :)

  • Crelo at 2017-05-04

    Well, Brady Daniels tells nice stories about the games, quite entertaining. It helps to learn a certain way of thinking during the games but to really understand what is happening one should read ahead like AlphaGo. 

    I like AlphaGo games but I don’t think humans can imitate it. I mean we can play the same moves but the games will still be messy, humans don’t know as well as AlphaGo when they are ahead and for sure don’t know so well the value of moves, not even professionals. I really think AlphaGo can now give at least two stones handicap to anybody, 

    He is correct about the ko :-)

  • lazyplayer at 2017-05-04

    Crelo, but is AlphaGo play correct or it is only “working” in self-play and again human players?

    Probably nobody knows but anyway the question is interesting. I think probably it’s indeed the right way to play and it should be copied.

  • lazyplayer at 2017-05-04

    To put the same idea in another way, counting territory accurately in Go is clearly necessary for near perfect play. But the same can’t be said for counting “centipawns” in chess.

  • Crelo at 2017-05-05

    Lazyplayer, there is no way to tell if the AI plays correct (perfect) moves or is just slightly better than us. There is also the danger to trust the AI too much, maybe there realy are better moves. We must get used to this new world. :-)

  • Florian Jamain at 2017-05-05

    Do you think the AI is capable to beat the best players in a long game?

    Something like 1 month per player.

    I would believe it only when I gonna see it. Now, I just believe the AI is capable to use the fact that humans gonna make mistakes cause of too short time.

  • lazyplayer at 2017-05-05

    Florian, but in reality it’s very hard for an human to remember the analysis already done. We’ve very bad short term memory. If you solve this problem then indeed humans should still be able to win when given enough time, i guess. Well, maybe you would need more time than their lifetimes... :)

  • Florian Jamain at 2017-05-05

    Then, if you prefer, you can do a match like this:

    150 of the bests humans are playing the same game against the AI, during a year. I guess it is enough.

    The goal is just to know if really the AI is playing better then humans in general. If there is no hope anymore. Cause finally it is the real question: Is the AI playing better than humans in the general sense.
    I don’t believe it, they will need to show me.

  • David J Bush at 2017-05-06

    Well Florian, I refer you back to the quote at the beginning of this thread. Pros are learning “new knowledge and strategy” from studying Alpha Go’s games. In the video, Hassabis briefly shows a couple of techniques that had previously been under-appreciated. If that’s not playing better than humans in the general sense, then what is?

  • Crelo at 2017-05-06

    Of course the AI is playing better, because it wins :-) AlphaGo is not an exception anymore, its software structure can be reproduced.

    https://qz.com/936654/googles-alpha-go-now-has-a-serious-game-playing-rival-with-tencents-jueyi-or-fineart/

    Anyway, the AI is still a human creation, we should feel proud, actually we will learn more this way.

  • Florian Jamain at 2017-05-06

    David, be sure that I don’t want to say that there is nothing to learn from AI or that AI is NEVER playing better than humans.
    This is completely different.

    My question is different. The fact is that AI in general are not playing “really” better with a lot of time to play, in a 2 hours or 3 hours game (per players), they are already playing very very well.
    A human is doing mistakes in a 2 hours game, these mistakes could be corrected in a 1 month game, the AI will also play better in a 1 month game but you can be sure that AI won’t play better as humans will.

    Crelo is agreeing with me, even if he does not realize it.
    He said that AI can give no more than 2 stones to best players in a 2 hours game, this almost implies that in a one month game humans can beat the AI.

  • Crelo at 2017-05-06

    I am afraid the computer will advance more in one month than humans.

  • Sighris at 2017-05-08

    When you give an AI significantly more time (assuming the computer resources are fully available) it can use all of that time; when you give humans more time they need to sleep & eat during some of that time... and if the AI programming were adjusted for the larger amount of time (again assuming the computer resources are fully available) think about how deeply the AI could probe into variations (I’m thinking about “brute force” checking of move choices made by the core process).  I’m with Crelo at 2017-05-06 ---> I think the computer AI would advance more than humans with the extra game time.

  • Carroll at 2017-05-22

    https://phys.org/news/2017-05-ready-rematch-machine-ancient-game.html

    It is tomorrow but I did not find if it will be streamed, anyone knows?

  • Arek Kulczycki at 2017-05-23

    The question that is the most interesting to me and also arises a couple of times here is “if AlphaGo plays better in general / if AlphaGo plays correctly”. The meaning of this is basically if AlphaGo plays better openings or just recovers in endgames.

    Experiment that should be done is:

    1) play N moves human vs AlphaGo
    2) finish that game AlphaGo vs AlphaGo
    3) assume that the winner played better opening
    4) try another N maybe

  • Tasmanian Devil at 2017-05-24

    It seems that nobody has spotted any particular weaknesses in AlphaGo’s opening play – or they would have exploited them. On occasion it plays surprising moves, but it does not mean they are bad, only that humans have not fully understood their benefits before. A top pro does not give away many points in the endgame anyway, so it needs to play good openings in order to win consistently.

    On Sensei’s Library they have started to collect joseki (local patterns) popularized by AlphaGo (I only looked at this briefly).

  • Arek Kulczycki at 2017-05-24

    I don’t know a thing about Go, but I assume that AlphaGo plays perfectly near ending when result is easier to compute. The only weakness should be first N moves, otherwise it may play perfectly all along.

  • lazyplayer at 2017-05-24

    Arek, i guess it depends on the game. Probably it’s like in Hex, where there are some very hard positions with many stones, but not that many.

  • lazyplayer at 2017-05-24

    And alphago “prudent” style probably allows it to play perfect when the position is favorable enough for one side.

  • Tasmanian Devil at 2017-05-24

    Arek – I think you may be underestimating the top pros. If AlphaGo made weak opening moves, they would attack the weaknesses mercilessly. Instead, they are analyzing its moves and considering to emulate the new strategies. It is true that finding correct moves towards the end may be easier for the computer, but then it is also easier for the humans.

    lazyplayer – AlphaGo probably plays best when it is only slightly ahead. If it is far ahead, it may be overly timid in order to secure the win rather than maximizing the score. When it is behind, it may try “wild” moves in order to try to shake off the opponent.

  • lazyplayer at 2017-05-24

    Tasmanian, how do you know that these “timid” moves aren’t in some sense the “best”?

    I think it’s a rational strategy, and humans can’t do it because they play more according to local patterns instead of playing according to the global state of the board.

  • Tasmanian Devil at 2017-05-24

    The objective of the game is to conquer as much territory+prisoners/area as possible. So the best move, if you could analyze any position perfectly, is the one that maximizes the score. But without the ability to analyze perfectly, the concept of risk enters the picture, and it makes sense to keep it small if you are ahead (whether you are a human or a computer program). Humans certainly consider risk when playing go. A safe play could be to secure your group/territory while allowing your opponent to do the same with theirs, while a risky play could be to dive into a big fight.

  • lazyplayer at 2017-05-24

    Eheh, no, objective is to have more points than opponent. Wide margin doesn’t matter.

    Yes they consider risk but they’ve less flexibility. They often have to play what they know is good in general (that is, good for balanced positions).

  • Tasmanian Devil at 2017-05-24

    So if the game is almost over, there are no uncertain complications left, you are ahead by 40 points, you can kill one of your opponent’s groups for 30 more points, or you can fill in an eye in one of your own groups, thus commit suicide and lose 30 points, these two moves are equally good?

  • lazyplayer at 2017-05-24

    Tasmanian, depends how you define “good”...

    Here we were debating perfect play near the end of the game, so it makes more sense to define “good” as “it makes sure that you preserve your win”.

  • lazyplayer at 2017-05-24

    Tasmanian, anyway maybe in the pursuit of safety, AlphaGo objectively gives away the win. Maybe. I’m waiting for commentary from people that actually are good at Go! :)

  • Tasmanian Devil at 2017-05-25

    You do that, and let me know if they disagree with anything I said here. 

  • Arek Kulczycki at 2017-05-26

    Tasmanian, let me clarify two things:

    1) I don’t underestimate pros – if anything maybe I overestimate AlphaGo. I say that AlphaGo either plays perfectly throughout or perfectly only near the end. It doesn’t say anything about the pros.

    2) I don’t say AlphaGo plays weakly in opening – I just say first N moves which may be first 300 moves if you just pick N = 300. My claim is that in a game that last K moves and K > N, AlphaGo plays better between Nth and Kth moves then between 1st and Nth.

    Hence it would be interesting to run AlphaGo vs AlphaGo starting from a position after N moves, for example of the second match against Ke Jie. Commentators said that it was close in the beginning.

  • mmKALLL ★ at 2017-05-26

    As a Go player, I don’t think that the assumption holds. What I mean is that I’m fairly confident that the advantage in opening can’t be determined by finishing the game with AlphaGo vs AlphaGo. Analysing with N > 50 also doesn’t really seem like it would give reliable enough data to understand the opening advantage.

    I’m saying this because I doubt that simply categorizing whether the AI is better in either the opening, the endgame, or in both is accurate enough. A more likely scenario would be that both humans and the AI have strenghts and weaknesses in all phases of the game – even in the endgame. The reading depth of top AI is not enough to crack the endgame reliably quite yet. Typically both top pros and AI play the last 40 or so moves nearly perfectly, rarely making a mistake of more than 0.75 points during the course of the endgame.

    In my opinion, the answer to your question is that AlphaGo both plays better in general, and with a higher degree of correctness. I’m not a researcher on the subject so do take my words with a grain of salt. However, I don’t think that the experiment setup you described would be able to answer the question convincingly enough; in my opinion relative skill in Go is not so binary that making conclusions from AlphaGo finishing board positions against itself would bring out the truth of the matter.

  • Crelo at 2017-05-28

    The summit in China is finished. I think we can tell Alphago is playing better opening and better middle game than Ke Jie. We don’t know for sure about te end game because Alphago is playing for safety once is ahead.

    50 games of Alphago against iteself were made public (http://www.alphago-games.com/). Impossible to understand them. My impression is that Alphago considers a 7.5p komi too big, Black is playing reckless moves, white seems more balanced, black won only 12 games.



  • lazyplayer at 2017-05-28

    Crelo, why “impossible to understand them”?

    I would expect that looking at (reliably and consistently) high quality games is very instructive.

  • lazyplayer at 2017-05-28

    And i would expect the stronger the players, the larger komi... why they’ve chosen 7.5? maybe it was closest to balanced (for AlphaGo) that they could find?

  • lazyplayer at 2017-05-28

    It’s also amusing that AlphaGo plays often 3-3 as answer to 4-4. It’s like in hex, hehe. We just want corner so badly :D

  • Crelo at 2017-05-28

    Impossible to understand means I cannot follow the logic behind the moves, someof them are against the current theory. We will have to unlearn first and try to understand after. Even so, the humans might not be able to play Alphago style because of limited and imperfect computational power.

  • Crelo at 2017-05-28

    Komi has nothing to do with the players strenght, it is just a number of points to compensate white to play second.

    It is true that komi increased in the last century because the advancements in the game theory. Korea and Japan are using a 6.5 komi, China is using 7.5. Because the chinese rules are counting areas instead of territories 6.5 is the same as 5.5 so they have to use 7.5

    The match with Ke Jie was played with chinese rules so 7.5 komi.

  • lazyplayer at 2017-05-28

    Crelo, yes, i know. It seems 6.5 komi under area scoring is not significantly higher than 5.5 komi.

    I guess the ideal would be 7 points in komi plus “Button Go” ;)

  • purgency at 2017-10-18

    https://deepmind.com/blog/alphago-zero-learning-scratch/

    “After just three days of self-play training, AlphaGo Zero emphatically defeated the previously published version of AlphaGo - which had itself defeated 18-time world champion Lee Sedol - by 100 games to 0. After 40 days of self training, AlphaGo Zero became even stronger, outperforming the version of AlphaGo known as “Master”, which has defeated the world's best players and world number one Ke Jie.” - from that article

  • wanderer_bot at 2017-10-18

    "It still required a huge amount of computing power — four of the specialized chips called tensor processing units, which Hassabis estimated to be US$25 million of hardware." — from the blurb

  • Tasmanian Devil at 2017-10-19

    The “old” AlphaGo seemed to win more often with white in self-play.  Perhaps the new version can tell us if the komi (7.5 with Chinese rules) is too high? (Strictly speaking, the correct komi should be an integer and correct play should give a draw, although many players probably would not like to open up for that.)

  • David J Bush at 2017-10-19

    Tasmanian, if a perfectly played game at komi 6.5 results in a black win, and a perfectly played game at komi 7.5 results in a white win, are you saying komi should be set at 7 and drawn games should be allowed? This would be a significant rules change which on a practical level would make the game less interesting IMO. There are other games which do not allow draws, such as Hex for example. Should the rules be changed for Hex as well?

    Even with such amazing improvements of Alpha Go Zero, no one is claiming to have solved Go. This is apparent from the fact that for a specific komi, with Zero playing both sides, sometimes black wins and sometimes white wins.

    A rules change I would like to see would be to adopt “komi pie.” Before the first stone is placed, one player sets the (non-integer) komi and the other player chooses which side to play. Get Alpha Go zero to set the komi by itself in this manner, and see what value it settles on after many games.

  • Tasmanian Devil at 2017-10-19

    Yes. I don’t personally agree that it would make the game less interesting, but I believe it is true that the go community would not want this change. I know it is not solved, but considering how strong the old version was, and given that this one is significantly stronger, its estimate of the optimal score should be somewhat reliable. We have a similar situation in Othello, where the estimated optimal score happens to be a draw.

    Hex does not really allow for draws as it is not game with a score, just obtaining a goal that is necessarily achieved sooner or later, and the swap rule appears to even out the odds pretty well.

  • purgency at 2017-10-19

    Sounds like a komi of 7.25 is the way to go. :))))))

  • purgency at 2017-10-19

    I have never seen or heard of anyone using the swap rule in go btw. Could be interesting to see something other than corner openings. Like choose the first move along with tie breaker +0.5 komi for either player and then the second guy can swap or not.

    It’s really not necessary to change the komi rules though. Whatever player you end up being you can win, because your opponent will not play correctly and thats for sure. I wouldn’t assume that a perfect game has ever even been played before.

  • David J Bush at 2017-10-19

    Well of course no perfect game has been played yet. And komi pie is effectively implemented on some servers, KGS for example. One person sets the parameters of the game including the komi, and whoever decides to play this person sometimes gets to choose which side to play. Setting the komi is a valid way to slice the pie all by itself, with no need to place an intial stone.

  • purgency at 2017-10-19

    Well, if the komi is set to 6.5 one will choose to play black, if its set to 7.5 one will choose white. I’m not sure if that even gets rid of anything unfair (not like it really is unfair anyway).

    The idea of using the swap rule instead of komi pie was more something I was curious about than something I find necessary. It deforms the game more I guess, since the first move is now not about finding the strongest move anymore, but one that is inbetween in strength, which might then snowball to the following moves and create an entirely new opening theory.

  • mmKALLL ★ at 2017-10-19

    I also really enjoy the swap rule for games like Gomoku or Polyomino, where you have a nice number of unorthodox openings available. I think swap would work well in Go, but for most players (let’s say 4 dan and less) the 1-point difference in komi is almost irrelevant with regards to the end result.

  • Carroll at 2017-11-02

    Have you seen this discussion about AlphaGo Zero:

    [–]HeyApples 30 points il y a 15 jours

    The small sample of AlphaGo vs. AlphaGo games published showed white winning a disproportionate amount of the time. Which led some to speculate that komi was too high.

    With access to a larger dataset, have you been able to make any interesting conclusions about the basic Go ruleset? (ie: Black or white have an intrinsic advantage, komi should be higher or lower, etc.)

    [–]JulianSchrittwieserDeepMind 23 points il y a 13 jours 

    In my experience and the experiments we’ve run, komi 7.5 is very balanced, we only observe a slightly higher winrate for white (55%).

    charger plus de commentaires (4 réponses)

    [–]SebastianDoyle 11 points il y a 14 jours 

    There is a video where Michael Redmond looks at a bunch of AG self-play games and says he thinks that the komi is right, and that White wins more games simply because AG is a stronger player as White than as Black. He gives some reasons for that, i.e. there are strategic differences in how to play White vs as Black, which AG apparently didn’t figure out. Looks like AG0 has caught up though :).

  • Sighris at 2017-11-20

    I agree with Tasmanian Devil's 2017-10-19 post: "Strictly speaking, the correct komi should be an integer [probably 7 based on JulianSchrittwieser of DeepMind and David J Bush 's 2017-10-19 post] and correct (perfect) play should give a draw (result in a tie game)... I don’t understand how anybody can argue with that other than “we want to make sure there are no ties because we want to buy only one 1st place trophy for the tournament.” - but I think that problem could be solved another way... and I think a finished game with a tie score would be a beautiful thing.  Although I can also imagine that perfect play with a whole number komi might not actually result in a tie game (even if Tasmanian Devil and I feel it “should”) for a reason something like (to oversimplify) the reason the game of Hex (or tic-tac-toe-3-in-a-row) cannot end in a tie. 

  • Carroll at 2017-11-20

    Ties are a problem because at high level, many games would end as ties as for example in chess.

    Then the other problem is how you value a tie compared with a win?

    Even in chess it is not easy and depends on the type of tournament and how the competition is doing, for deciding whether you should aim for a more aggressive (and risky) strategy.

    I think there is a parameter in Stockfish for that but there was no agreement on how to set it because it should depend on the strength of the opponent.

  • Tasmanian Devil at 2017-11-20

    The problem with Chess is that draws are all too common. In the candidates tournament 2016, Giri played 14 remis in a row! In games where draws are possible but not that common, like Go with integer komi or Othello, I don’t see any big problems. If two players have played equally well, why should the colour they happened to play decide the winner? Ties for first place are possible even if draws are not possible: three players may have beaten each other cyclically. And here on Little Golem there was an example of an Amazons tournament with five players tied for first place!

  • Luis BolaNos at 2017-11-21

    The solution, as lazyplayer said, is to play Button Go with komi 7. The button is a special token worth 0.5 points. At any point, instead of making a regular move, a player can take the button, provided that none of the players has taken it before. (Officially, taking the button lifts ko and superko bans, but I’m not sure it should.)

    It’s interesting to note that Button Go with komi 7 is either virtually or fully equivalent to Go with komi 6.5 under territory scoring, depending on how you define territory scoring and whether you consider that taking the button lifts ko and superko bans or not.

  • Luis BolaNos at 2017-11-21

    Just to be clear: button Go is meant to be played with area scoring, which is what AlphaGo uses. Under territory scoring, komi 6 plus button always gives the same result as komi 6.5 without button, and fractional komi is simpler.

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