4 ms·

Even if it is 100% deterministic (which I'm not convinced of, especially seeing as how distributed and thus ordering-dependent it is), if it's the best in the w

Even if it is 100% deterministic (which I'm not convinced of, especially seeing as how distributed and thus ordering-dependent it is), if it's the best in the world, how does that help you compete against it? In order to take advantage of its determinism you'd need to be better than it, and nothing else is.

dragontamer 7y ago
> if it's the best in the world, how does that help you compete against it? In order to take advantage of its determinism you'd need to be better than it, and nothing else is. Play AlphaGo against itself. Go rarely has draws (requires Triple-Ko, a very, very rare position). Almost every game you play with AlphaZero vs AlphaZero will result in a winner-and-loser. You will quickly be able to characterize the positions that AlphaZero loses in.
- CydeWeys 7y ago
  But if you're not as least as good at it you won't even be able to get to those positions. You'll lose to it much earlier in much worse ways.
  - dragontamer 7y ago
    The cyborg player will have access to the best publicly available software for preparation a year ahead of any competition. For most of us, that means we'll all have the best verison of LeelaZero to grab from Github and use in our own personal studies. Which should still be super-human in terms of play.
    - CydeWeys 7y ago
      How is the human player adding anything to this partnership when the program is already so much better? And don't forget that AlphaZero is gonna be getting better over that year too; you're trying to beat a moving target.
- 1123581321 7y ago
  Go engine training surpasses this basic level of self-play effectively instantly. The strongest early moves create the most potential for winning (maximizing potential winning paths, sort of); they do not push the game towards one best end state. They do not have counters. I saw elsewhere you have some understanding of the game (15kyu) so you should be able to demonstrate this to yourself by playing some of AlphaGo’s openings on a board and trying to write deterministic counters to them. You will not be able to push the AI into a situation where it has too few options to avoid loss. You will also find you need to create a book much larger than a few moves to meaningfully predict play and so will exceed the number of states that can be stored (referencing your 16TB comment elsewhere.) Please actually try this as I think it is a key to improving your skill in addition to understanding the challenges in automating play.

dragontamer 7y ago

> if it's the best in the world, how does that help you compete against it? In order to take advantage of its determinism you'd need to be better than it, and nothing else is. Play AlphaGo against itself. Go rarely has draws (requires Triple-Ko, a very, very rare position). Almost every game you play with AlphaZero vs AlphaZero will result in a winner-and-loser. You will quickly be able to characterize the positions that AlphaZero loses in.

CydeWeys 7y ago
But if you're not as least as good at it you won't even be able to get to those positions. You'll lose to it much earlier in much worse ways.
- dragontamer 7y ago
  The cyborg player will have access to the best publicly available software for preparation a year ahead of any competition. For most of us, that means we'll all have the best verison of LeelaZero to grab from Github and use in our own personal studies. Which should still be super-human in terms of play.
  - CydeWeys 7y ago
    How is the human player adding anything to this partnership when the program is already so much better? And don't forget that AlphaZero is gonna be getting better over that year too; you're trying to beat a moving target.
1123581321 7y ago
Go engine training surpasses this basic level of self-play effectively instantly. The strongest early moves create the most potential for winning (maximizing potential winning paths, sort of); they do not push the game towards one best end state. They do not have counters. I saw elsewhere you have some understanding of the game (15kyu) so you should be able to demonstrate this to yourself by playing some of AlphaGo’s openings on a board and trying to write deterministic counters to them. You will not be able to push the AI into a situation where it has too few options to avoid loss. You will also find you need to create a book much larger than a few moves to meaningfully predict play and so will exceed the number of states that can be stored (referencing your 16TB comment elsewhere.) Please actually try this as I think it is a key to improving your skill in addition to understanding the challenges in automating play.