Re: [Computer-go] Our Silicon Overlord

On 06.01.2017 23:37, Jim O'Flaherty wrote: into a position with superko [...] how do you even get AlphaGo into a the arcane state in the first place, I can't in practice. I have not provided a way to beat AlphaGo from the game start at the empty board. All I have shown is that there are

Re: [Computer-go] Our Silicon Overlord

Okay. So I will play along. How do you think you would coax AlphaGo into a position with superko without AlphaGo having already simulated that pathway as a less probable win space for itself when compared to other playing trees which avoid it? IOW, how do you even get AlphaGo into a the arcane

Re: [Computer-go] it's alphago

To my knowledge, fishtest is also a major part of stockfish engine. It is essential because there is lot of possible improvement and most of them win only 2 or 3 elo points, but added, it lead to 60-70 elo points between each release (every one year or something like that) Le 06/01/2017 à 17:22,

Re: [Computer-go] it's alphago

Ray was Japanese student program that went on 7th, UEC cup 2016. Ray http://computer-go-ray.com/eng/index.html Thare is a stronger version of Ray, with policy net and value net. https://github.com/zakki/Ray/tree/nn CGOS BayesElo is 3463 (Rn.3.3-4c). http://www.yss-aya.com/cgos/19x19/bayes.html

Re: [Computer-go] it's alphago (How to get a strong value network)

Hi, If I understood correctly you would try to use a program using value net with (let's say 2000 playouts) in selfplay? Using only one result, or Yes. 2000 playouts/move MCTS with policy net and value net. doing some games per position? Or are you thinking of using only the win I thought

Re: [Computer-go] it's alphago

Oh sorry I mispoke, corporate players losing interest is a bad thing in my mind but also more or less inevitable(to some degree anyway). I was simply saying that as delighted as I am that google and other players are putting so much money and research into go I suspect eventually the resources

Re: [Computer-go] it's alphago

And why would it be desirable that 'the big corporate players lose interest to devote computer power'? And who are those big corporate players? Deepmind? Who are not even selling their bot? Or are you talking about CS/Zen who are having indeed financial interests here? What would be the benefit of

Re: [Computer-go] it's alphago

A closer example than the mersenne prime search is fishtest from the chess engine world. My understanding is that it is a key part of why stockfish is such a strong chessengine. https://github.com/glinscott/fishtest A large group of volunteers that essentially donate compute power to test

Re: [Computer-go] it's alphago

A project similar to the Great Mersenne Prime search might be a possibility to distribute the work of training the network among many enthousiasts, and to keep improving it by self play. On 1/6/17, Andy wrote: > What is Ray? Strongest open source bot? Anyone have a link

Re: [Computer-go] it's alphago

What is Ray? Strongest open source bot? Anyone have a link to it? On Fri, Jan 6, 2017 at 3:39 AM, Hiroshi Yamashita wrote: > If value net is the most important part for over pro level, the problem is > making strong selfplay games. > > 1. make 30 million selfplay games. > 2.

Re: [Computer-go] it's alphago

Maybe now we need AlphaGo vs. Tartrate to see who is the definitive Sai XD 2017-01-06 6:39 GMT-03:00 Hiroshi Yamashita : > If value net is the most important part for over pro level, the problem is > making strong selfplay games. > > 1. make 30 million selfplay games. > 2.

Re: [Computer-go] it's alphago (How to get a strong value network)

Hi, this sounds interesting! AlphaGo paper plays only with RL network, if I understood correctly. If we start this huge approach we should try to carefully discuss the way (and hopefully get some hints from people tried with much computational power :) If I understood correctly you would try to