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Lee Sedol Beats AlphaGo in Game 4

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Re: Lee Sedol Beats AlphaGo in Game 4

#141

Earlier quoted context omitted.

In that case, theoretically at least, we could train AlphaGo by getting top Go players to play many games against each other where one or both players is making very aggressive moves when reasonable?

Well, that's where AlphaGo and the progress in Go AI that it represents is so exciting ! The game of Go is so fluid with such a huge number of possible positions that players tend to adopt certain styles of play en masse . I've heard it said that you can identify a Go player's mentor or "house" just by the style of play they use. This has also resulted in larger shifts in playing style over time. Studying very old (a…

AlphaGo will learn from any new styles and apply them effectively without mistakes from fatigue or inattention.

This incarnation of AI is not creative, it wont generate new play styles, that is still the domain of top human players for now. But it will ruthlessly learn and adopt any new and improved strategies. That's really the point to take away from its success so far.

Re: Lee Sedol Beats AlphaGo in Game 4

#142
post #108

Earlier quoted context omitted.

From my limited knowledge of the game, a few of the moves that Lee made before AlphaGo "lost its mind" were a tad on the aggressive side. The conventional wisdom in Go is to prefer more conservative moves (increasingly so as the game progresses). Usually, if your opponent is being overly aggressive then you want to play more conservatively and wait for them to make a mistake, but in AlphaGo's case, it attempted to ma…

> If I had to guess (and this is pure speculation), AlphaGo has no concept of waiting for its opponent to make a mistake. Instead, it assumes its opponent will continue to make the best possible follow-ups One of the DeepMind guys just confirmed that this is how AlphaGo operates in the press conference.

Which makes sense. It doesn't even have a concept of a human opponent or human-style mistakes - it plays against Lee just like it plays against itself when training.

Re: Lee Sedol Beats AlphaGo in Game 4

#143

So AlphaGo is just a bot after all... Toward the end AlphaGo was making moves that even I (as a double-digit kyu player) could recognize as really bad. However, one of the commentators made the observation that each time it did, the moves forced a highly-predictable move by Lee Sedol in response. From the point of view of a Go player, they were non-sensical because they only removed points from the board and didn't a…

I'm curious - is this the same thing that it was doing in the matches that it won? People have been talking about how it seemed to be toying with its opponent towards the end of those matches, making moves that didn't gain it much, but maybe it just doesn't actually understand what moves to play some of the time and it simply hasn't mattered before.

Re: Lee Sedol Beats AlphaGo in Game 4

#144

In the post-game press conference I think Lee Sedol said something like "Before the matches I was thinking the result would be 5-0 or 4-1 in my favor, but then I lost 3 straight... I would not exchange this win for anything in the world." Demis Hassabis said of Lee Sedol: "Incredible fighting spirit after 3 defeats" I can definitely relate to what Lee Sedol might be feeling. Very happy for both sides. The fact that p…

I've read some articles in Korean press that suggested AlphaGo team picked Lee as their match and not Ke Jie (currently #1 ranked, 19 years young) because there's a lot more public records of Lee's plays over his much longer pro career (nearly 20 years now). Thus more material for AlphaGo to train with and against. So it's not totally arrogant of Ke Jie to suggest he could beat AlphaGo. AlphaGo has not much 'experien…

That was specifically discussed in the after match conference today. Demis said that it wasn't trained specifically against Lee but was trained against strong amateurs on the Internet initially before playing against itself. He said that even if they'd wanted to, alpha go requires a much larger number of games than are available by Lee Seoul to train so it wouldn't have been possible anyway.

Re: Lee Sedol Beats AlphaGo in Game 4

#145

Relevant tweets from Demis; Lee Sedol is playing brilliantly! #AlphaGo thought it was doing well, but got confused on move 87. We are in trouble now... Mistake was on move 79, but #AlphaGo only came to that realisation on around move 87 When I say 'thought' and 'realisation' I just mean the output of #AlphaGo value net. It was around 70% at move 79 and then dived on move 87 Lee Sedol wins game 4!!! Congratulations! H…

Just in case someone wants the commentary around this move 78

https://www.youtube.com/watch?v=yCALyQRN3hw&t=11413

Re: Lee Sedol Beats AlphaGo in Game 4

#147
post #78

If it's true that AlphaGo started making a series of bad moves after its mistake on move 79, this might tie into a classic problem with agents trained using reinforcement learning, which is that after making an initial mistake (whether by accident or due to noise, etc.), the agent gets taken into a state it's not familiar with, so it makes another mistake, digging an even deeper hole for itself - the mistakes then co…

There is a possibility that the AlphaGo team, knowing that it has already won a decisive victory, wanted to spare the champion a crushing 5-0 defeat and so commanded the AI to lose on purpose.

[deleted]

Re: Lee Sedol Beats AlphaGo in Game 4

#148
post #60

Am I right by asumming, that if they would play another game (AlphaGo black and Lee Sedol white), that Lee Sedol could pressure AlphaGo into makeing the same mistake again?

This is an interesting question - if Lee Sedol simply replays the game exactly, does he repeat a win? I think the answer would be most likely not - the monte carlo tree search is randomized so AlphaGo's responses to Sedol may not be exactly the same, requiring Sedol to not be able to repeat the exact same play.

Assuming it's a parallel monte carlo computation i doubt it would make exactly the same moves.

Re: Lee Sedol Beats AlphaGo in Game 4

#149

In the post-game press conference I think Lee Sedol said something like "Before the matches I was thinking the result would be 5-0 or 4-1 in my favor, but then I lost 3 straight... I would not exchange this win for anything in the world." Demis Hassabis said of Lee Sedol: "Incredible fighting spirit after 3 defeats" I can definitely relate to what Lee Sedol might be feeling. Very happy for both sides. The fact that p…

I've read some articles in Korean press that suggested AlphaGo team picked Lee as their match and not Ke Jie (currently #1 ranked, 19 years young) because there's a lot more public records of Lee's plays over his much longer pro career (nearly 20 years now). Thus more material for AlphaGo to train with and against. So it's not totally arrogant of Ke Jie to suggest he could beat AlphaGo. AlphaGo has not much 'experien…

Err, so if AlphaGo wins game 5, does that show 'an AI is still indeed more capable than any human?'

Re: Lee Sedol Beats AlphaGo in Game 4

#150

Earlier quoted context omitted.

I've read some articles in Korean press that suggested AlphaGo team picked Lee as their match and not Ke Jie (currently #1 ranked, 19 years young) because there's a lot more public records of Lee's plays over his much longer pro career (nearly 20 years now). Thus more material for AlphaGo to train with and against. So it's not totally arrogant of Ke Jie to suggest he could beat AlphaGo. AlphaGo has not much 'experien…

That was specifically discussed in the after match conference today. Demis said that it wasn't trained specifically against Lee but was trained against strong amateurs on the Internet initially before playing against itself. He said that even if they'd wanted to, alpha go requires a much larger number of games than are available by Lee Seoul to train so it wouldn't have been possible anyway.

It was discussed pre-match for game 2 or 3 as well, and Lee's games were described as "a drop in the ocean" I believe.

Came up because of an assertion from the interviewer that chess AI had been trained against it's opponent specifically.

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