How AlphaZero Mastered Its Games
newyorker.com
How AlphaZero Mastered Its Games
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Re: How AlphaZero Mastered Its Games
#2They mention a documentary on Netflix about AlphaGo. Any recommendations for or against?
Re: How AlphaZero Mastered Its Games
#3James put together a really nice summary of the ideas and the projects!
It was almost a year ago that lc0 was launched, since then the community (led by Alexander Lyashuk, author of the current engine) has taken it to a totally different level. Follow along at http://lczero.org!
Gcp has also done an amazing job with Leela Zero, with a very active community on the Go side. http://zero.sjeng.org
Of course, DeepMind really did something amazing with AlphaZero. It’s hard to overstate how dominant minimax search has been in chess. For another approach (MCTS/NN) to even be competitive with 50+ years of research is amazing. And all that without any human knowledge!
Still, Stockfish keeps on improving - Stockfish 10 is significantly stronger than the version AlphaZero played in the paper (no fault of DeepMind; SF just improves quickly). We need a public exhibition match to setttle the score, ideally with some GM commentary :). To complete the links you can watch Stockfish improve here: http://tests.stockfishchess.org.
Re: How AlphaZero Mastered Its Games
#4They mention a documentary on Netflix about AlphaGo. Any recommendations for or against?
I heard it’s good from several people. I haven’t seen it myself yet.
Re: How AlphaZero Mastered Its Games
#5James put together a really nice summary of the ideas and the projects! It was almost a year ago that lc0 was launched, since then the community (led by Alexander Lyashuk, author of the current engine) has taken it to a totally different level. Follow along at http://lczero.org ! Gcp has also done an amazing job with Leela Zero, with a very active community on the Go side. http://zero.sjeng.org Of course, DeepMind re…
I thought alphazero was based on minimax, and used neural networks to evaluate moves, isn't this the case ?
Re: How AlphaZero Mastered Its Games
#6They mention a documentary on Netflix about AlphaGo. Any recommendations for or against?
It's good. Like, not for the algorithmic side, but the emotional side. It is very accessible even when you cannot work with computers.
Re: How AlphaZero Mastered Its Games
#7James put together a really nice summary of the ideas and the projects! It was almost a year ago that lc0 was launched, since then the community (led by Alexander Lyashuk, author of the current engine) has taken it to a totally different level. Follow along at http://lczero.org ! Gcp has also done an amazing job with Leela Zero, with a very active community on the Go side. http://zero.sjeng.org Of course, DeepMind re…
I thought alphazero was based on minimax, and used neural networks to evaluate moves, isn't this the case ?
It is kind of the case, but it does not need to expand the whole node to find the maximum. It samples some children instead from a NN (the Monte Carlo aspect)
Re: How AlphaZero Mastered Its Games
#8James put together a really nice summary of the ideas and the projects! It was almost a year ago that lc0 was launched, since then the community (led by Alexander Lyashuk, author of the current engine) has taken it to a totally different level. Follow along at http://lczero.org ! Gcp has also done an amazing job with Leela Zero, with a very active community on the Go side. http://zero.sjeng.org Of course, DeepMind re…
I thought alphazero was based on minimax, and used neural networks to evaluate moves, isn't this the case ?
MCTS is not a traditional depth first minimax framework. Key concepts like alpha-beta don’t apply. Although it is proven to converge to minimax in the limit, the game trees are so large this is not relevant. You could use the network in a minimax searcher, but it’s so much slower than a conventional evaluation function it’s unlikely to be competitive.
Re: How AlphaZero Mastered Its Games
#9They mention a documentary on Netflix about AlphaGo. Any recommendations for or against?
I enjoyed it. It's not super technical, but it does a great job of telling the story and getting you caught up in the emotions of the people involved.
Re: How AlphaZero Mastered Its Games
#10James put together a really nice summary of the ideas and the projects! It was almost a year ago that lc0 was launched, since then the community (led by Alexander Lyashuk, author of the current engine) has taken it to a totally different level. Follow along at http://lczero.org ! Gcp has also done an amazing job with Leela Zero, with a very active community on the Go side. http://zero.sjeng.org Of course, DeepMind re…
I strongly suspect alphazero is easily beatable, once you have your hands on it. This is just from experience that most neural network style systems are weak against adversarial opponents who understand their internals.
Of course I can't be sure, because Google refuses to give out anyone access to alphazero, or a network trained with it. Personally, that gives me more confidence they know there are significant exploitable weaknesses.