Re: [Computer-go] dealing with multiple local optima

[Erik van der Werf]

On Mon, Feb 27, 2017 at 4:30 PM, Darren Cook  wrote:

> > But those video games have a very simple optimal policy. Consider Super
> Mario:
> > if you see an enemy, step on it; if you see a whole, jump over it; if
> you see a
> > pipe sticking up, also jump over it; etc.
>
> A bit like go? If you see an unsettled group, make it live. If you have
> a ko, play a ko threat. If you see have two 1-eye groups near each
> other, join them together. :-)
>
> Okay, those could be considered higher-level concepts, but I still
> thought it was impressive to learn to play arcade games with no hints at
> all.
>


The impressive part is hidden in what most humans consider trivial; to make
the programs 'see'

Erik
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Re: [Computer-go] dealing with multiple local optima

[Darren Cook]

> But those video games have a very simple optimal policy. Consider Super 
> Mario: 
> if you see an enemy, step on it; if you see a whole, jump over it; if you see 
> a 
> pipe sticking up, also jump over it; etc.

A bit like go? If you see an unsettled group, make it live. If you have
a ko, play a ko threat. If you see have two 1-eye groups near each
other, join them together. :-)

Okay, those could be considered higher-level concepts, but I still
thought it was impressive to learn to play arcade games with no hints at
all.

Darren


> 
> On Sat, Feb 25, 2017 at 12:36 AM, Darren Cook  > wrote:
> 
>  > ...if it is hard to have "the good starting point" such as a trained
>  > policy from human expert game records, what is a way to devise one.
> 
> My first thought was to look at the DeepMind research on learning to
> play video games (which I think either pre-dates the AlphaGo research,
> or was done in parallel with it): https://deepmind.com/research/dqn/
> 
> 
> It just learns from trial and error, no expert game records:
> 
> 
> http://www.theverge.com/2016/6/9/11893002/google-ai-deepmind-atari-montezumas-revenge
> 
> 
> 
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[Computer-go] March KGS bot tournament - slow

[Nick Wedd]

The March KGS bot tournament will start on Sunday, March 5th, starting at
22:00 UTC and end by 14:00 UTC on Wednesday 8th.  It will use 19x19 boards,
with time limits of 235 minutes each plus fast Canadian overtime, and komi
of 7½.  That's four hours each, so each round will take eight hours.

It will be a Swiss tournament, with eight rounds.  See
*https://www.gokgs.com/tournInfo.jsp?id=1100
*

Please register by emailing me at mapr...@gmail.com, with the words "KGS
Tournament Registration" in the email title.

Nick
-- 
Nick Wedd  mapr...@gmail.com
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