Live data from Hacker News

Lee Sedol Beats AlphaGo in Game 4

gogameguru.com

41–50 of 471 posts

Re: Lee Sedol Beats AlphaGo in Game 4

#42

I was hoping to see how AlphaGo would play in overtime. Now I'm curious, does it know how to play in overtime? Can the system handle evaluating how much time it can give itself to 'think' about each move, or does it fall into the halting problem territory and it was programmed to evaluate its probability of winning given the 'fixed' time it had left.

They've been in overtime before. In game 2 I think. AlphaGo spent about 30 seconds on each move

Re: Lee Sedol Beats AlphaGo in Game 4

#44

I was hoping to see how AlphaGo would play in overtime. Now I'm curious, does it know how to play in overtime? Can the system handle evaluating how much time it can give itself to 'think' about each move, or does it fall into the halting problem territory and it was programmed to evaluate its probability of winning given the 'fixed' time it had left.

It was in overtime in game 2, I believe. It did fine.

Re: Lee Sedol Beats AlphaGo in Game 4

#45
post #27

That was really cool! It seemed after the brilliant play in the middle the most probable moves for winning required Lee Sedol to make impossibly bad mistakes for a professional, which would be a prior that AlphaGo doesn't incorporate. I've heard the training data was mostly amateur games so perhaps the value/policy networks were overfit? Or maybe greedily picking the highest probability, common with tree search appro…

I think it's more that the value network includes moves which look plausible but won't concentrate around the answer to a forcing move as having >99% probability. A human has a heuristic: "I must play here else I lose" but AG assumes its opponent might play anywhere that the ANN calls reasonable.

Re: Lee Sedol Beats AlphaGo in Game 4

#46

I was hoping to see how AlphaGo would play in overtime. Now I'm curious, does it know how to play in overtime? Can the system handle evaluating how much time it can give itself to 'think' about each move, or does it fall into the halting problem territory and it was programmed to evaluate its probability of winning given the 'fixed' time it had left.

It's called scorboarding. You start coming up with solutions and ranking them and putting the best one up on the scoreboard. When you run out of time, you just go with what you got. Pretty much what humans have.

I'm sure there are many levels of watchdogs in this program.

Re: Lee Sedol Beats AlphaGo in Game 4

#47
post #34

Earlier quoted context omitted.

The thing is, Lee Sedol didn't "find the right moves"; the wedge at L11 shouldn't have worked. If black's 79th move had been at L10 instead of K10, Sedol would likely have resigned on the spot.

As far as I can tell from watching Redmond's commentary at the time, there were other options for white in the area.

I was on the other stream; Myungwan Kim and Hajin Lee went way deeper than Redmond typically goes (since they have access to an SGF editor instead of a clumsy demo board, and they aren't performing for the camera as much). They seemed pretty confident in their conclusion that L10 killed white.

Re: Lee Sedol Beats AlphaGo in Game 4

#48
After AlphaGo won the first three games, I wondered not if the computer had reached and surpassed human mastery, but instead how many orders of magnitude better it was. Given today's result, it may be only one order, or even less. Perhaps the best human players are relatively close to the maximum skill level for go, and that the pros of the future will not be categorically better than Lee Sedol is today.

Re: Lee Sedol Beats AlphaGo in Game 4

#49
post #19

Earlier quoted context omitted.

According to the head of DeepMind, AlphaGo made a mistake in evaluating move 79: https://twitter.com/demishassabis/status/708928006400581632

> Mistake was on move 79, but #AlphaGo only came to that realisation on around move 87 That's cool to think of AlphaGo having "realizations"

[deleted]
Post reply on HN