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What is interesting to me is that the computer makes clear mistakes when its on the lead. Since it might find the chances to win equally among different scoring

What is interesting to me is that the computer makes clear mistakes when its on the lead. Since it might find the chances to win equally among different scoring results, it often picks a weaker one. This has a powerful consequence: we have not seen AlphaGo pushed to the limit, he is lowering the distances as if it were playing a teaching game. Lee Sedol I think came to this conclusion, and the only human strategy left is to take a lead big enough to maintain the rest of the game. And that might be the last strategy to play to show the computer is already unbeatable, because it will be pushed to its limits to win a game and it might overcome humans.

taneq 11y ago
I don't see how you can term them as "clear mistakes" when the game is playing at a higher level than any of us meatbags. In this case (according to DeepMind) it's no different to a racing driver backing off the pace in the last few laps if they have a big lead - it's better to guarantee a win than to win by a large margin.
- conanbatt 11y ago
  You might be confusing correctness with relevance. You can pass at the last move and lose 1 point, but if your lead is 5, its the same win-result but not the same count-result. Well, that would be a mistake by all accounts, even if AlphaGo made it. Some of the moves AlphaGo played both in this game and the previous one are very definite mistakes, but they were irrelevant to the difference in the game.
  - w0bb13 11y ago
    Alphago isn't programmed to think of that as a mistake (i.e. the team wouldn't be disappointed if she did it). It really only cares about W/L.
    - conanbatt 11y ago
      If you redefine a mistake as not a mistake, you only uncover that the path to perfection is denial.
  - cjbprime 11y ago
    > Well, that would be a mistake by all accounts, even if AlphaGo made it. It is only a mistake to your human biases. AlphaGo literally has no conception of the margin of a win. It doesn't care either way how many points it wins by, as long as the win percentage is maximized.
    - awhe 11y ago
      I think that his point is that it would be interesting to see AlphaGo pushed to its limit and playing a point-maximizing game. Which would be pretty terrifying.
    - taneq 11y ago
      Exactly. It's actually a pretty common behaviour for tree-searching game playing algorithms. Unless they're set up to explicitly give weight to faster wins or higher margin wins, they get into an unassailable position and then just kind of dick around. If every move's a win then it doesn't matter which move you make, right?
KVFinn 11y ago
>What is interesting to me is that the computer makes clear mistakes when its on the lead. Since it might find the chances to win equally among different scoring results, it often picks a weaker one. When they interviewed the devs briefly, they said this is because AlphaGo doesn't really consider the score other whan winning, so it will pick a move it think is an 81% chance to win by one stone over an 80% chance to win by 10 stones. When it's ahead these moves can look like mistakes but a better way of describing them would be hedging.

taneq 11y ago

I don't see how you can term them as "clear mistakes" when the game is playing at a higher level than any of us meatbags. In this case (according to DeepMind) it's no different to a racing driver backing off the pace in the last few laps if they have a big lead - it's better to guarantee a win than to win by a large margin.

conanbatt 11y ago
You might be confusing correctness with relevance. You can pass at the last move and lose 1 point, but if your lead is 5, its the same win-result but not the same count-result. Well, that would be a mistake by all accounts, even if AlphaGo made it. Some of the moves AlphaGo played both in this game and the previous one are very definite mistakes, but they were irrelevant to the difference in the game.
- w0bb13 11y ago
  Alphago isn't programmed to think of that as a mistake (i.e. the team wouldn't be disappointed if she did it). It really only cares about W/L.
  - conanbatt 11y ago
    If you redefine a mistake as not a mistake, you only uncover that the path to perfection is denial.
- cjbprime 11y ago
  > Well, that would be a mistake by all accounts, even if AlphaGo made it. It is only a mistake to your human biases. AlphaGo literally has no conception of the margin of a win. It doesn't care either way how many points it wins by, as long as the win percentage is maximized.
  - awhe 11y ago
    I think that his point is that it would be interesting to see AlphaGo pushed to its limit and playing a point-maximizing game. Which would be pretty terrifying.
  - taneq 11y ago
    Exactly. It's actually a pretty common behaviour for tree-searching game playing algorithms. Unless they're set up to explicitly give weight to faster wins or higher margin wins, they get into an unassailable position and then just kind of dick around. If every move's a win then it doesn't matter which move you make, right?

KVFinn 11y ago

>What is interesting to me is that the computer makes clear mistakes when its on the lead. Since it might find the chances to win equally among different scoring results, it often picks a weaker one. When they interviewed the devs briefly, they said this is because AlphaGo doesn't really consider the score other whan winning, so it will pick a move it think is an 81% chance to win by one stone over an 80% chance to win by 10 stones. When it's ahead these moves can look like mistakes but a better way of describing them would be hedging.