Re: [computer-go] Congratulations to David Fotland!

So, when are we going to see distributed computing? [EMAIL PROTECTED], [EMAIL PROTECTED], [EMAIL PROTECTED] With Go engines that scale well to increased processing capacity, imagine facilitating a few thousand PCs to do the computing. For good measure, [EMAIL PROTECTED] as about 800,000 nodes

Re: [computer-go] [EMAIL PROTECTED]

I think I'll respond here as not to further detract from David congratulory thread. :) While not addressing the replies separately, rest assured that I've read them all. Quickly picking up on what Claus wrote here, I agree that there might be some kind of prestige angle to exploit to get some

Re: [computer-go] Congratulations to David Fotland!

Hideki Kato wrote: Don Dailey: [EMAIL PROTECTED]: On Thu, 2008-10-02 at 19:17 +0200, Michael Markefka wrote: So, when are we going to see distributed computing? [EMAIL PROTECTED], [EMAIL PROTECTED], [EMAIL PROTECTED] With Go engines that scale well to increased processing capacity, imagine

Re: [computer-go] [EMAIL PROTECTED]

Brilliant! Thank you, both of you, Peter and Claus! -Mike Claus Reinke wrote: Now, for the technical matter: Could somebody please point me to a quick rundown of how modern Go engines exactly utilize multicore environments and the workload is segregated and distributed? I don't have any

Re: [Computer-go] Fwd: Teaching Deep Convolutional Neural Networks to Play Go

I was thinking about bootstrapping possibilities, and wondered whether it would be possible to use a shallower mimic net for positional evaluation playouts from a specific depth on after having generated positions with a certain branching factor that typically allows the actual pro move to be

Re: [Computer-go] Standalone DNN player support

I would love to have something like this. I would appreciate some way to configure depth levels and variable branching factors for move generation as well as scoring playouts using the NN. Regards, Michael On Wed, Apr 29, 2015 at 3:37 PM, Josef Moudrik j.moud...@gmail.com wrote: Hi! I am

Re: [Computer-go] CNN with 54% prediction on KGS 6d+ data

Hello Detlef, I've got a question regarding CNN-based Go engines I couldn't find anything about on this list. As I've been following your posts here, I thought you might be the right person to ask. Have you ever tried using the CNN for complete playouts? I know that CNNs have been tried for move

Re: [Computer-go] CNN with 54% prediction on KGS 6d+ data

ould be the way. >>> > >>> > Josef >>> > >>> > On Tue, Dec 8, 2015 at 5:17 PM Petr Baudis <pa...@ucw.cz> wrote: >>> > >>> > > Hi! >>> > > >>> > > In case someone is looking for a sta

Re: [Computer-go] CNN with 54% prediction on KGS 6d+ data

<weiqiprogramm...@gmail.com> wrote: > I doubt that the illegal moves would fall away since every professional > would retake the ko... if it was legal > > > On 2015-12-09 4:59, Michael Markefka wrote: >> >> Thank you for the feedback, everyone. >> >

Re: [Computer-go] Creating the playout NN

Might be worthwhile to try the faster, shallower policy network as a MCTS replacement if it were fast enough to support enough breadth. Could cut down on some of the scoring variations that confuse rather than inform the score expectation. On Sun, Jun 12, 2016 at 10:56 AM, Stefan Kaitschick

Re: [Computer-go] Creating the playout NN

rain a model with many > parameters, you have enough to train a model with fewer parameters. > > Álvaro. > > > On Sun, Jun 12, 2016 at 5:52 AM, Michael Markefka < > michael.marke...@gmail.com> wrote: > >> Might be worthwhile to try the faster, shallower poli

Re: [Computer-go] Timetable "Computers and Games 2016"

Aya, thank you for giving us some insight into AlphaGo. We are all very much looking forward to it On Wed, Jun 22, 2016 at 5:29 PM, Aja Huang wrote: > > > 2016-06-22 12:29 GMT+01:00 "Ingo Althöfer" <3-hirn-ver...@gmx.de>: >> >> Hi, >> >> the timetable for the conference

Re: [Computer-go] Timetable "Computers and Games 2016"

A_j_a, of course. Sorry for messing this up. On Wed, Jun 22, 2016 at 8:27 PM, Michael Markefka <michael.marke...@gmail.com> wrote: > Aya, thank you for giving us some insight into AlphaGo. We are all > very much looking forward to it > > On Wed, Jun 22, 2016 at 5:29 PM

Re: [Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search (value network)

That sounds like it'd be the MSE as classification error of the eventual result. I'm currently not able to look at the paper, but couldn't you use a softmax output layer with two nodes and take the probability distribution as winrate? On Thu, Feb 4, 2016 at 8:34 PM, Álvaro Begué

Re: [Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search

On Thu, Jan 28, 2016 at 3:14 PM, Stefan Kaitschick wrote: > That "value network" is just amazing to me. > It does what computer go failed at for over 20 years, and what MCTS was > designed to sidestep. Thought it worth a mention: Detlef posted about trying to train

Re: [Computer-go] Game Over

I find it interesting that right until he ends his review, Antti only praises White's moves, which are the human ones. When he stops, he even considers a win by White as basically inevitable. Now Fan Hui either blundered badly afterwards, or more promising, it could be hard for humans to evaluate

Re: [Computer-go] Game Over

That would make my writing nonsense of course. :) Thanks for the pointer. On Thu, Jan 28, 2016 at 12:26 PM, Xavier Combelle <xavier.combe...@gmail.com> wrote: > > > 2016-01-28 12:23 GMT+01:00 Michael Markefka <michael.marke...@gmail.com>: >> >> I find it interes

Re: [Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search

be more than satisfied. On Thu, Jan 28, 2016 at 7:42 AM, Robert Jasiek <jas...@snafu.de> wrote: > Congratulations to the researchers! > > On 27.01.2016 21:10, Michael Markefka wrote: >> >> I really do hope that this also turns into a good analysis and >> teaching

Re: [Computer-go] Computer-go Digest, Vol 72, Issue 41

I agree. It might be interesting to set this up a while after the Lee Sedol matches if Ke Jie still holds the #1 spot at at that time. After beating the best player of the past ten years, beating the currently best player would in a way complete AlphaGo's victory over current human Go ability.

Re: [Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search

On Mon, Feb 1, 2016 at 10:19 AM, Darren Cook wrote: > It seems [1] the smart money might be on Lee Sedol: In the DeepMind press conferences ( https://www.youtube.com/watch?v=yR017hmUSC4 - https://www.youtube.com/watch?v=_r3yF4lV0wk ) Demis Hassabis stated, that he was quietly

Re: [Computer-go] Zen19X achieved stable KGS 7d

On Mon, Feb 1, 2016 at 1:44 PM, Hideki Kato wrote: > I was, btw, really surprised when Zen beat fj with two stones > handi. > http://files.gokgs.com/games/2016/1/31/Zen19X-fj.sgf > > Hideki On the DGoB forums fj stated, possibly in jest, that this was an even game, as he

Re: [Computer-go] Mastering the Game of Go with Deep Neural Networks and Tree Search

I really do hope that this also turns into a good analysis and teaching tool for human player. That would be a fantastic benefit from this advancement in computer Go. On Wed, Jan 27, 2016 at 9:08 PM, Aja Huang wrote: > 2016-01-27 18:46 GMT+00:00 Aja Huang

[Computer-go] Move evalution by expected value, as product of expected winrate and expected points?

Hello everyone, in the wake of AlphaGo using a DCNN to predict expected winrate of a move, I've been wondering whether one could train a DCNN for expected territory or points successfully enough to be of some use (leaving the issue of win by resignation for a more in-depth discussion). And,

Re: [Computer-go] computergo.org

Not a definite solution yet, but more of a call to action here: Would anyone be interested contributing to a well-maintained computer go news site? I would consider that a useful service that is currently lacking. I'd be happy to contribute news articles and links. On Thu, Mar 17, 2016 at 4:16

Re: [Computer-go] Deep Zen - do we have a race now?

Hi Petr, to clarify a bit: pylearn2 specifically comes with a script to convert a model trained on a GPU into a version that runs on the CPU. This doesn't work very well though and the documentation points that out too. According to the dev commens that is down to how Theano, the framework

Re: [Computer-go] Deep Learning learning resources?

This online book by Michael Nielsen is a fantastic resource: http://neuralnetworksanddeeplearning.com/ It builds everything from the ground up in easily digested chunks. All the required math is in there, but can be skipped if just a general understanding and basis for application is desired.

Re: [Computer-go] new challenge for Go programmers

Then again DNNs also manage feature extraction on unlabeled data with increasing levels of abstraction towards upper layers. Perhaps one could apply such a specifically trained DNN to artificial board situations that emphasize specific concepts and examine the network's activation, trying to map

Re: [Computer-go] Hajin Lee will play a live commented game against CrazyStone

That is awesome! Looking forward to it! On Mon, May 16, 2016 at 9:50 AM, Rémi Coulom wrote: > Hi, > > I am very happy to announce that Hajin Lee will play a live commented game > against Crazy Stone on Sunday, at 8PM Korean time. The game will take place > on KGS, and she

Re: [Computer-go] OmegaGo

Can I flag this as spam? On Tue, Apr 19, 2016 at 11:23 PM, djhbrown . wrote: > 6D out of the blue is no mean achievement,... 60+ years ago, the > market for gizmos in UK was flooded with cheap Japanese copies of > European products; but whilst innovation and product quality

Re: [Computer-go] Deep Zen vs Cho Chikun -- Round 3

That sounds very promising. Any chance some of the improvements will filter down into the current commercial version in the form of update patches? On Wed, Nov 23, 2016 at 11:03 PM, Hideki Kato wrote: > Thanks David. > > It's now. > > In the same afternoon, Zen vs Yonil

Re: [Computer-go] Go Tournament with hinteresting rules

> > > The basic explanation for why this is not straightforward is that you > never want your program to consider moves in the direction of > low-probability wins, no matter how large margins they might have; the > MC measurement function is very noisy with regards to individual samples. > I do

Re: [Computer-go] World Go Championship

Just a wild guess, but I assume they'll go for the latest winner of the UEC Cup as far as AI entrants are concerned. On Tue, Nov 29, 2016 at 3:46 PM, "Ingo Althöfer" <3-hirn-ver...@gmx.de> wrote: > Hi Hideki, > > that sounds very interesting. > > > Nihon Kiin created a new Go tournament, "World

Re: [Computer-go] Project Leela Zero

That looks very interesting. Looking forward to some implementation of this filtering down to the common ML libs. On Mon, Mar 19, 2018 at 2:39 PM, Stefan Kaitschick wrote: > Is this something LeelaZero might consider using? > https://arxiv.org/pdf/1803.05407.pdf > The