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Am 06.12.2015 um 16:24 schrieb Petr Baudis:
> On Sat, Dec 05, 2015 at 02:47:50PM +0100, Detlef Schmicker wrote:
>> I understand the idea, that long term prediction might lead to a
>> different optimum (but it should not lead to one with a higher
>>
On Sat, Dec 05, 2015 at 02:47:50PM +0100, Detlef Schmicker wrote:
> I understand the idea, that long term prediction might lead to a
> different optimum (but it should not lead to one with a higher one
> step prediction rate: it might result in a stronger player with the
> same prediction rate...)
> I understand the idea, that long term prediction might lead to a
> different optimum (but it should not lead to one with a higher one
> step prediction rate: it might result in a stronger player with the
> same prediction rate...), and might increase training speed, but hard
> facts would be grea
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Hi,
I'd like to start some discussion again.
The Title "Better Computer Go Player with Neural Network and Long-term
Prediction" seems to put the focus on Long-term Prediction, but my
Problem is, that I can not find the result from the paper.
My main
On Tue, Nov 24, 2015 at 01:39:00PM +0100, Petr Baudis wrote:
> On Mon, Nov 23, 2015 at 10:00:27PM -0800, David Fotland wrote:
> > 1 kyu on KGS with no search is pretty impressive.
>
> But it doesn't correlate very well with the reported results against
> Pachi, it seems to me.
>
> ("Pachi 10k" sh
Yamashita
- Original Message -
From: "Yuandong Tian"
To:
Sent: Wednesday, November 25, 2015 5:45 AM
Subject: Re: [Computer-go] Facebook Go AI.
Hi all,
I am the first author of Facebook Go AI. Thanks for your interest! This is
the first time I post a message here, so please
> An: computer-go@computer-go.org
> Betreff: Re: [Computer-go] Facebook Go AI.
>
> Hi all,
>
> I am the first author of Facebook Go AI. Thanks for your interest! This is
> the first time I post a message here, so please forgive me if I mess up
> with anything.
>
>
Perhaps bots in the style of Darkforest would be good
candidates to win the Handicap-29 prize...
http://www.althofer.de/handicap-29-prize.html
Ingo.
***
Gesendet: Dienstag, 24. November 2015 um 07:00 Uhr
Von: "David Fotland"
1 ky
Hi all,
I am the first author of Facebook Go AI. Thanks for your interest! This is
the first time I post a message here, so please forgive me if I mess up
with anything.
1. The estimation of 1d-2d is based on the win rate of free game in the
last 3 months (since darkforest launched in Aug). See T
If you train your neural network on pro games, pros never play out
ladders that end up in capture, so when a ladder situation happens and
it gets played out, the running group is always safe. This is not the
case always, but you'd need to specifically play out the ladder to check.
On 2015-11-2
That can happen if the bot has a big (and strange) weak point such as
ladder. See attached record.
Hideki
Petr Baudis: <20151124123900.gm10...@machine.or.cz>:
>On Mon, Nov 23, 2015 at 10:00:27PM -0800, David Fotland wrote:
>> 1 kyu on KGS with no search is pretty impressive.
>
>But it doesn't c
On Mon, Nov 23, 2015 at 10:00:27PM -0800, David Fotland wrote:
> 1 kyu on KGS with no search is pretty impressive.
But it doesn't correlate very well with the reported results against
Pachi, it seems to me.
("Pachi 10k" should correspond to ~5s thinking time on 8-thread FX8350.)
> Perhaps Darkfo
1 kyu on KGS with no search is pretty impressive. Perhaps Darkforest2 is too
slow.
David
From: Computer-go [mailto:computer-go-boun...@computer-go.org] On Behalf Of Andy
Sent: Monday, November 23, 2015 9:48 AM
To: computer-go
Subject: Re: [Computer-go] Facebook Go AI
As of about an
As of about an hour ago darkforest and darkfores1 have started playing
rated games on KGS!
2015-11-23 11:28 GMT-06:00 Andy :
> So the KGS bots darkforest and darkfores1 play with only DCNN, no MCTS
> search added? I wish they would put darkfores2 with MCTS on KGS, why not
> put your strongest bo
So the KGS bots darkforest and darkfores1 play with only DCNN, no MCTS
search added? I wish they would put darkfores2 with MCTS on KGS, why not
put your strongest bot out there?
2015-11-23 10:38 GMT-06:00 Petr Baudis :
> The numbers look pretty impressive! So this DNN is as strong as
> a full-
The numbers look pretty impressive! So this DNN is as strong as
a full-fledged MCTS engine with non-trivial thinking time. The increased
supervision is a nice idea, but even barring that this seems like quite
a boost to the previously published results? Surprising that this is
just thanks to relat
It is darkforest, indeed:
Title: Better Computer Go Player with Neural Network and Long-term
Prediction
Authors: Yuandong Tian, Yan Zhu
Abstract:
Competing with top human players in the ancient game of Go has been a
long-term goal of artificial intelligence. Go's high branching factor
makes
ladder. Maybe pure DCNN without MC search?
darkforest is ver 1.0, darkfores1 is ver 1.1. a bit latest.
Regards,
Hiroshi Yamashita
- Original Message -
From: "Nick Wedd"
To:
Sent: Wednesday, November 04, 2015 4:32 AM
Subject: Re: [Computer-go] Facebook Go AI
I think this F
It loses games to kyu-players because it does not mark their stones as dead
at the game end. Some kyu players mark them for it, but others are happy to
accept an undeserved win.
While it does not mark dead stones, it will not be assigned KGS "rated bot"
status, to prevent dishonest players from us
Thanks for that observation Nick!
For those that don't want to look for themselves:
https://www.gokgs.com/gameArchives.jsp?user=darkforest
https://www.gokgs.com/gameArchives.jsp?user=darkfores1
>From a quick look it seems like it is winning most of its games, even
against 1d/2d players, but ther
I think this Facebook AI may be the program playing on KGS as darkforest
and darkfores1.
Nick
On 3 November 2015 at 14:28, Petr Baudis wrote:
> Hi!
>
> Facebook is working on a Go AI too, now:
>
> https://www.facebook.com/Engineering/videos/10153621562717200/
> https://code.
This looks like GnuGo at level 1. Note things like filling at Q15, which GnuGo
would not do on level 10 or higher.
Cheers,
David G Doshay
ddos...@mac.com
> On 3, Nov 2015, at 8:31 AM, Marc Landgraf wrote:
>
> then again, Gnugo donked that game pretty badly.
> Showing one game, where Gnug
then again, Gnugo donked that game pretty badly.
Showing one game, where Gnugo just throws away the entire top before move
50 is not really telling about the overall strength, imho. Gnugo repeats
the failure by suiciding the top right as well.
What is shown after is hard to evaluate, considering th
Can a strong player look at the video and give impressions about the game?
On 11/03/2015 03:28 PM, Petr Baudis wrote:
Hi!
Facebook is working on a Go AI too, now:
https://www.facebook.com/Engineering/videos/10153621562717200/
https://code.facebook.com/posts/14785235124784
Hi!
Facebook is working on a Go AI too, now:
https://www.facebook.com/Engineering/videos/10153621562717200/
https://code.facebook.com/posts/1478523512478471
http://www.wired.com/2015/11/facebook-is-aiming-its-ai-at-go-the-game-no-computer-can-crack/
The way it's pres
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