[Computer-go] Accelerating Self-Play Learning in Go

Hi, I have just found out that the list is not sending emails to my free.fr email address any more. So I subscribed with my gmail address, which I hope should work better. I had missed that very interesting message by David Wu ( http://computer-go.org/pipermail/computer-go/2019-March/010991.html)

Re: [Computer-go] Accelerating Self-Play Learning in Go

On 8/03/19 16:14, David Wu wrote: > I suspect Leela Zero would come off as far *less* favorable if one > tried to do such a comparison using their actual existing code rather > than abstracting down to counting neural net evals, because as far as > I know in Leela Zero there is no cross-game batchi

Re: [Computer-go] Accelerating Self-Play Learning in Go

>> contrary to intuition built up from earlier-generation MCTS programs in Go, >> putting significant weight on score maximization rather than only >> win/loss seems to help. This narrative glosses over important nuances. Collectively we are trying to find the golden mean of cost efficiency...

Re: [Computer-go] Accelerating Self-Play Learning in Go

On Fri, Mar 8, 2019 at 8:19 AM Darren Cook wrote: > > Blog post: > > https://blog.janestreet.com/accelerating-self-play-learning-in-go/ > > Paper: https://arxiv.org/abs/1902.10565 > > I read the paper, and really enjoyed it: lots of different ideas being > tried. I was especially satisfied to see

Re: [Computer-go] Accelerating Self-Play Learning in Go

> Blog post: > https://blog.janestreet.com/accelerating-self-play-learning-in-go/ > Paper: https://arxiv.org/abs/1902.10565 I read the paper, and really enjoyed it: lots of different ideas being tried. I was especially satisfied to see figure 12 and the big difference giving some go features made

Re: [Computer-go] Accelerating Self-Play Learning in Go

From before AlphaGo was announced, I thought the way forward was generating games that play to the bitter end maximizing score, and then using the final ownership as something to predict. I am very glad that someone has had the time to put this idea (and many others!) into practice. Congratulations

[Computer-go] Accelerating Self-Play Learning in Go

For any interested people on this list who don't follow Leela Zero discussion or reddit threads: I recently released a paper on ways to improve the efficiency of AlphaZero-like learning in Go. A variety of the ideas tried deviate a little from "pure zero" (e.g. ladder detection, predicting board o