AlphaGo beats Lee Sedol 3-0 [video]

Post by joelthelion » Sat, Mar 12, 2016, 4:25 PM UTC

Eliezer wrote: post #79

My (long) commentary here: https://www.facebook.com/yudkowsky/posts/10154018209759228 Sample: At this point it seems likely that Sedol is actually far outclassed by a superhuman player. The suspicion is that since AlphaGo plays purely for probability of long-term victory rather than playing for points, the fight against Sedol generates boards that can falsely appear to a human to be balanced even as Sedol's probabili…

Post by Melkman » Sat, Mar 12, 2016, 4:32 PM UTC

21 wrote: post #122

School-Cotton wrote: post #97

Earlier quoted context omitted.

> Of course, a cat is not conscious. How do you know?

I'm not an expert in this domain, but I think it's pretty much scientific consensus that this is the case. Now experts can discuss details or semantics, but do you truly suggest cats might be conscious?

Post by moyix » Sat, Mar 12, 2016, 4:40 PM UTC

YeGoblynQueenne wrote: post #314

moyix wrote: post #310

Earlier quoted context omitted.

I think you're wrong here. From the Nature paper describing AlphaGo: "We also tested against the strongest open-source Go program, Pachi, a sophisticated Monte Carlo search program, ranked at 2 amateur dan on KGS, that executes 100,000 simulations per move. Using no search at all, the RL policy network won 85% of games against Pachi." AlphaGo does use MCTS, but it seems that most of its improvements are actually comi…

I don't know whether this is true. If AlphaGo could do just as well without search, then why did it use search at all? But in any case, I'm not necessarily disputing that. I'm particularly refuting the claim that the AlphaGo architecture is identical to the one that learned to play Atari games and that Deepmind have advertised as a general game-playing agent. My comment here is specifically in reply to the GP who rep…

Post by [deleted] » Sat, Mar 12, 2016, 4:46 PM UTC

moyix wrote: post #310

YeGoblynQueenne wrote: post #304

Earlier quoted context omitted.

>> AlphaGo's core is built around a similar machine learning technology to Deepmind's Atari-playing system - the single, untweaked program that was able to learn superhuman play on dozens of different Atari games just by looking at the pixels, without specialization for each particular game. Woa there. The Deepmind Atari-playing AI was too specialised for each particular game. It had a reward function that translated…

I think you're wrong here. From the Nature paper describing AlphaGo: "We also tested against the strongest open-source Go program, Pachi, a sophisticated Monte Carlo search program, ranked at 2 amateur dan on KGS, that executes 100,000 simulations per move. Using no search at all, the RL policy network won 85% of games against Pachi." AlphaGo does use MCTS, but it seems that most of its improvements are actually comi…

Post by hacker42 » Sat, Mar 12, 2016, 4:52 PM UTC

YeGoblynQueenne wrote: post #314

moyix wrote: post #310

Earlier quoted context omitted.

I think you're wrong here. From the Nature paper describing AlphaGo: "We also tested against the strongest open-source Go program, Pachi, a sophisticated Monte Carlo search program, ranked at 2 amateur dan on KGS, that executes 100,000 simulations per move. Using no search at all, the RL policy network won 85% of games against Pachi." AlphaGo does use MCTS, but it seems that most of its improvements are actually comi…

I don't know whether this is true. If AlphaGo could do just as well without search, then why did it use search at all? But in any case, I'm not necessarily disputing that. I'm particularly refuting the claim that the AlphaGo architecture is identical to the one that learned to play Atari games and that Deepmind have advertised as a general game-playing agent. My comment here is specifically in reply to the GP who rep…