Hi Magnus,
thanks also to you for your experiments.
In particular, I like you setting with integral komi.
Cheers, Ingo.
> Gesendet: Samstag, 11. November 2017 um 00:48 Uhr
> Von: valky...@phmp.se
> An: Computer-go@computer-go.org
> Betreff: [Computer-go] Update Odin Zero 9x9 Komi 7.
>
> Odin
On Fri, Nov 10, 2017 at 03:40:27PM +0100, Gian-Carlo Pascutto wrote:
> On 10/11/2017 1:47, Petr Baudis wrote:
>
> > * AlphaGo used 19 resnet layers for 19x19, so I used 7 layers for 7x7.
>
> How many filters per layer?
256 like AlphaGo.
> FWIW 7 layer resnet (14 + 2 layers) is still pretty
Odin has now generated 5 games with 100 simulation and 90% prior for
a random move, and 1 games with 5000 simulations and 15% prior for a
random move, with temperature 1.
The network has been trained all the time and the loss function is now
dropping about 0.02 units every 10 hours or
On 10/11/2017 1:47, Petr Baudis wrote:
> * AlphaGo used 19 resnet layers for 19x19, so I used 7 layers for 7x7.
How many filters per layer?
FWIW 7 layer resnet (14 + 2 layers) is still pretty huge - larger than
the initial AlphaGo. Given the amount of games you have, and the size of
the
It's a model written using the Keras neural network library:
https://en.wikipedia.org/wiki/Keras
On Fri, Nov 10, 2017 at 7:09 AM, Xavier Combelle
wrote:
> You make me really curious,
> what is a Keras model ?
>
> Le 10/11/2017 à 01:47, Petr Baudis a écrit :
> > Hi,
> You make me really curious, what is a Keras model ?
When I was a lad, you had to bike 3 miles (uphill in both directions) to
the library to satisfy curiosity. Nowadays you just type "keras" into
Google ;-)
https://keras.io/
Darren
___
Computer-go
You make me really curious,
what is a Keras model ?
Le 10/11/2017 à 01:47, Petr Baudis a écrit :
> Hi,
>
> I got first *somewhat* positive results in my attempt to reproduce
> AlphaGo Zero - 25% winrate against GNUGo on the easiest reasonable task
> - 7x7 board. :) a.k.a.
>
>
On Fri, Nov 10, 2017 at 01:47:17AM +0100, Petr Baudis wrote:
> This is a truly "zero-knowledge" system like AlphaGo Zero - it needs
> no supervision, and it contains no Monte Carlo simulations or other
> heuristics. But it's not entirely 1:1, I did some tweaks which I thought
> might help early