Re: [Computer-go] MiniGo open sourced

2018-01-30 Thread Gian-Carlo Pascutto
On 30-01-18 20:59, Álvaro Begué wrote:
> Chrilly Donninger's quote was probably mostly true in the 90s, but
> it's now obsolete. That intellectual protectionism was motivated by
> the potential economic profit of having a strong engine. It probably
> slowed down computer chess for decades, until the advent of strong
> open-source programs. Paradoxically, when the economic incentive to
> create strong engines was removed, we saw an explosion in strength.

There still seems to be an economic incentive to improve [1] strong
engines and try to sell them.

It should be noted that until Stockfish came along, open source computer
chess engines were a graveyard where every strong enough engine just got
cloned or plagiarized and real enduring cooperation was essentially
nonexistent. You just had 10 non-cooperating forks (some closed source,
and some allegedly commercial ones) that added <-20 ... >+100 Elo.

There had been open source engines as early as GNUChess (or probably
earlier...), and very strong ones like Fruit.

I don't know for sure what allowed Stockfish to (mostly) escape the same
fate. Right now I would say fishtest is a huge factor, but it might've
been doing fine before that.

[1] I originally wrote "create" here but that might not be correct.

-- 
GCP
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Re: [Computer-go] MiniGo open sourced

2018-01-30 Thread Álvaro Begué
Chrilly Donninger's quote was probably mostly true in the 90s, but it's now
obsolete. That intellectual protectionism was motivated by the potential
economic profit of having a strong engine. It probably slowed down computer
chess for decades, until the advent of strong open-source programs.
Paradoxically, when the economic incentive to create strong engines was
removed, we saw an explosion in strength.

Álvaro.


On Tue, Jan 30, 2018 at 2:14 PM, "Ingo Althöfer" <3-hirn-ver...@gmx.de>
wrote:

> Hi,
>
> GCP wrote:
> > ...
> > > Of course, in the end, strength is the best way to tell that your
> > > implementation is correct :)
> >
> > In other words, do not take "correct" as necessarily meaning "matching
> > the published research".
>
> Chrilly Donnninger, one of the computer chess gurus in the 1990's and
> the early 200x's (project Hydra) had an expressed opinion:
> "Those who know, do not publish.
> And those who publish do not know."
> He himself violated this rule in the early 1990's when he published
> a price-winning paper on how to implement null-move search correctly.
>
> Ingo.
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Re: [Computer-go] MiniGo open sourced

2018-01-30 Thread Ingo Althöfer
Hi,

GCP wrote:
> ... 
> > Of course, in the end, strength is the best way to tell that your 
> > implementation is correct :)
> 
> In other words, do not take "correct" as necessarily meaning "matching
> the published research".

Chrilly Donnninger, one of the computer chess gurus in the 1990's and
the early 200x's (project Hydra) had an expressed opinion:
"Those who know, do not publish.
And those who publish do not know."
He himself violated this rule in the early 1990's when he published
a price-winning paper on how to implement null-move search correctly.

Ingo.
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Re: [Computer-go] MiniGo open sourced

2018-01-30 Thread Gian-Carlo Pascutto
On 30-01-18 02:50, Brian Lee wrote:
> We're not aiming for a top-level Go AI; we're merely aiming for a 
> correct, very readable implementation of the AlphaGoZero algorithm

I had a look around to see how you resolved what I'd consider the
ambiguities in the original paper:
https://github.com/gcp/leela-zero/issues/785

> Of course, in the end, strength is the best way to tell that your 
> implementation is correct :)

In other words, do not take "correct" as necessarily meaning "matching
the published research".

-- 
GCP
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Re: [Computer-go] MiniGo open sourced

2018-01-30 Thread Ingo Althöfer
Dear Brian,

thank you for your posting and for publishing
the MiniGo code.
 
> I'm happy to announce MiniGo is now open source.
> https://github.com/tensorflow/minigo
>
> We're ... aiming for a correct, very readable implementation 
> of the AlphaGoZero algorithm and demonstration of Google 
> Cloud / Kubernetes / TensorFlow. ...

Hopefully, others will use your code also for attacking
other games with simple rules, like Clobber, ConHex (by
Michail Antonow), or Yavalath (by Cameron Browne/Ludohex).
 
> A few Googlers, including myself and Andrew Jackson, have 
> been working on this, but we're otherwise completely 
> unaffiliated with DeepMind and the AlphaGo project.
 
May you tell us, in which Google lab you are working?

Thanks again for your contribution!
Ingo.
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