In particular, they had no way to train a value net, so it was back to
AlphaGo v1 style of training just a policy net and reusing it as the
rollout policy.
On Fri, Apr 6, 2018 at 6:31 AM Fidel Santiago wrote:
> Hello,
>
> Apparently the lessons of Alphago (and many others) are being applied to
On Tue, Nov 3, 2009 at 6:43 AM, Willemien wrote:
> I disagree with the point that MCTS is a neural network,
>
> In my opinion (and i maybe completely off target) One of the essences
> of neural networks is that the program changes/learns from the games
> it has played. .
I think that you are righ
these things have definitions, folks.
everything isn't everything else.
s.
On Tue, Nov 3, 2009 at 7:43 AM, Willemien wrote:
> I disagree with the point that MCTS is a neural network,
>
> In my opinion (and i maybe completely off target) One of the essences
> of neural networks is that the progr
I disagree with the point that MCTS is a neural network,
In my opinion (and i maybe completely off target) One of the essences
of neural networks is that the program changes/learns from the games
it has played. .
MCTS doesn't have that result, the improvement is only "in-game"
The program doesn't
Well, at its esence a computer is an universal Turing Machine. If you
organize the program as a neural network or as a MC algorithm is just
cosmetics.
You can see the circuits of your computer as neurons simulating a Von
Neumann architecture that is simulating a neural network or a MC or
whatever.
On Sun, Nov 1, 2009 at 7:50 PM, Aldric Giacomoni wrote:
> Álvaro Begué wrote:
>> 2009/10/31 :
>>> Present day MC Go programs are neural networks. The playout is the trainng
>>> process.
>>
>> What?
>> ___
>> computer-go mailing list
>> computer-go@compu
Álvaro Begué wrote:
> 2009/10/31 :
>> Present day MC Go programs are neural networks. The playout is the trainng
>> process.
>
> What?
> ___
> computer-go mailing list
> computer-go@computer-go.org
> http://www.computer-go.org/mailman/listinfo/computer-
2009/10/31 :
> Present day MC Go programs are neural networks. The playout is the trainng
> process.
What?
___
computer-go mailing list
computer-go@computer-go.org
http://www.computer-go.org/mailman/listinfo/computer-go/
Present day MC Go programs are neural networks. The playout is the trainng
process.
DL
-Original Message-
From: Petr Baudis
To: computer-go@computer-go.org
Sent: Wed, Oct 14, 2009 7:26 am
Subject: [computer-go] Neural networks
Hi!
Is there some "high-level reason" hypothesised
On Wed, Oct 14, 2009 at 05:12:58PM +0200, Heikki Levanto wrote:
> On Wed, Oct 14, 2009 at 03:34:59PM +0300, Petri Pitkanen wrote:
> > Neural network tend to work well in those cases where evaluation function is
> > smooth, like backgammon. Even inbackgammon neural networks do give good
> > results
> support-vector machines, neural networks have been considered completely
> obsolete in the machine-learning community. From a marketing point of
> view, it is not a good idea to do research on neural networks nowadays.
> You must give your system another name.
That seems to be the case in the ac
[ Digression: Some ANN architectures are more biologically plausible than
others. "Neuromorphic Engineering" is a good search term to see what's going on
along those lines. (But for a beginner project, the standard multi-layer
perceptron with backpropogation would still be the natural choice.)
;
>
> David
>
>> -Original Message-
>> From: computer-go-boun...@computer-go.org [mailto:computer-go-
>> boun...@computer-go.org] On Behalf Of Rémi Coulom
>> Sent: Wednesday, October 14, 2009 6:07 AM
>> To: computer-go
>> Subject: Re: [computer-go] Ne
David Fotland wrote:
Remi, what do you think of Numenta http://www.numenta.com/, a startup that
is using feedforward/feedback networks to model learning and pattern
recognition in the neocortex. Does this approach make sense or is it just
startup hype?
http://www.numenta.com/for-developers/edu
I'm not Remi, but I know a bit about Numenta. I gave a "lightning
talk" at their
workshop about a year and a half ago. A few people at Numenta are
interested
in using their software for Go, and I was working with one of them
before my
heart problems stopped that work.
I do not think that th
-background-htm.ph
p
David
> -Original Message-
> From: computer-go-boun...@computer-go.org [mailto:computer-go-
> boun...@computer-go.org] On Behalf Of Rémi Coulom
> Sent: Wednesday, October 14, 2009 6:07 AM
> To: computer-go
> Subject: Re: [computer-go] Neural networks
>
Neural networks are not considered obsolete by the machine learning
community; in fact there is much active research on neural networks
and the term is understood to be quite general. SVMs are linear
classifiers for hand-engineered features. When a single layer of
template-matchers isn't enough,
On Wed, Oct 14, 2009 at 03:34:59PM +0300, Petri Pitkanen wrote:
> Neural network tend to work well in those cases where evaluation function is
> smooth, like backgammon. Even inbackgammon neural networks do give good
> results if situation has possibility of sudden equity changes like deep
> backga
Petr Baudis wrote:
Hi!
Is there some "high-level reason" hypothesised about why there are
no successful programs using neural networks in Go?
I'd also like to ask if someone has a research tip for some
interesting Go sub-problem that could make for a nice beginner neural
networks project.
I guess neural networks is fine for learning pattern priorities for
example. There are probably just simpler and faster methods for doing
that.
Anyway a good project would be learning 3x3 patterns for MC heavy
playouts with a large number of extra features such as exact liberty
counts, di
On Wed, Oct 14, 2009 at 02:45:18PM +0200, Erik van der Werf wrote:
> In my opinion NeuroGo was quite succesful with neural networks.
> Magog's main strength came from neural networks. Steenvreter uses
> 'neural networks' to set priors in the Monte Carlo Tree.
Ah, you are right, that sounds like fa
In my opinion NeuroGo was quite succesful with neural networks.
Magog's main strength came from neural networks. Steenvreter uses
'neural networks' to set priors in the Monte Carlo Tree.
Erik
On Wed, Oct 14, 2009 at 2:26 PM, Petr Baudis wrote:
> Hi!
>
> Is there some "high-level reason" hypot
Neural network tend to work well in those cases where evaluation function is
smooth, like backgammon. Even inbackgammon neural networks do give good
results if situation has possibility of sudden equity changes like deep
backgames and deep anchor games. Top backgammon programs 3-ply search on top
n
The initial patterns are, of course, bitmaps of the board. When a nonzero
signal finally arrives at cell #5, one of the 1-bits is randomly selected
as the move. (If that turns out illegal, the actual move is "pass.")
Without understanding everything about what you're doing (not even
close), I'm
George Dahl said:
> FANN (http://leenissen.dk/fann/) is a great neural network library
> written in C. I don't know much about books on *programming* neural
> networks specifically, but I know of many great books on neural
> networks. I am a big fan of Bishop's Neural Networks for Pattern
> Recog
On 7/20/07, Joshua Shriver <[EMAIL PROTECTED]> wrote:
Anyone recommend a good book on programming Neural Networks in C or C++?
Been digging around the net for while and haven't come up with
anything other than an encyclopedia-like definition/writeup. No
examples or tutorials.
There are some C
FANN (http://leenissen.dk/fann/) is a great neural network library
written in C. I don't know much about books on *programming* neural
networks specifically, but I know of many great books on neural
networks. I am a big fan of Bishop's Neural Networks for Pattern
Recognition even if you aren't n
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