You can get most articles through Sci-Hub
<https://plus.google.com/u/0/+RussAbbott1/posts/5YGik2SsyDV>. The Nature
piece is available here
<http://sci-hub.io/http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html>.
Amazing!

-- Russ

On Mon, Mar 14, 2016 at 3:38 PM Robert J. Cordingley <[email protected]>
wrote:

> Access, for a fee, to the original Jan, 2016 Nature article on AlpahGo is
> at http://www.nature.com/nature/journal/v529/n7587/full/nature16961.html.
> The freely available abstract says it uses deep neural networks ('value
> networks' and 'policy networks'), tree search and Monte Carlo algorithms.
> Figures and tables with more information are also freely available from
> http://www.nature.com/nature/journal/v529/n7587/fig_tab/nature16961_ft.html
>
> Robert C
>
>
> On 3/13/16 8:53 PM, Steve Smith wrote:
>
> Me, I'm still stuck in the 80's... most of what I know about GO programs
> involves trying to solve them using cellular automata systems based on the
> promise of hardware implementations and other esoteric ways of doing CA
> computation...   Tomasso Toffolli's custom CA hardware was one promising
> thing that I think eventually fizzled as was our own Jim Crutchfield's
> analog "video feedback" CA computing concepts...
>
> My own favorite which I went on to do some exploratory work in was the
> "memoisation" work of Bill Gosper which involves generating hash tables at
> each scale (say 3x3, 6x6, 12x12, 24x24) cell arrays such that if
> "redundant" patterns occurred at any scale they could be "looked up"
> instead of computed.   In a 3x3 (9 cell) array, there are naturally only
> 512 (2^9) hash indices so the computation at that level is manageable by
> memoisation... while a 6x6 is 2^36 or roughly 64M entries, not quite so
> tractable/trivial if the distribution of possible configurations of binary
> CA were uniform...  which interesting GO configurations naturally are
> NOT.   A slight modification to this is that a binary CA is not sufficient
> since the states of each cell can be White/Black/Empty... so the math
> changes to 4^9 and 4^26,etc...
>
> Similar attempts were made for checkers and chess which as I remember, the
> state space for Checkers is much larger than for Chess (surprising?) but
> GO... much higher (larger board!) and the depth (number of relevant moves
> ahead) also much higher!
>
> I look forward to hearing what the current state of computer GO play might
> look like as well!
>
> - Steve
>
>
> There were stories during the expert systems episode in the 80's that some
> experts when debriefed in an attempt to identify their rules went on to
> lose faith in their own expertise and to resign from the field. Other
> anecdotes talked about how some experts weren't capable of expressing their
> expertise - such knowledge, skills & experience was referred to as
> 'compiled knowledge', accessible but not expressible, much like Artificial
> Neural Networks are. Work
> <http://www.sciencedirect.com/science/article/pii/0950705196819204> to
> address this problem has been underway since the 90's. Perhaps others here
> can provide an update?
>
> Robert C
>
> On 3/13/16 8:45 AM, Marcus Daniels wrote:
>
> I think a deep neural network trained from self play has a subjective, and 
> even inscrutable inner representation.  Imagine such techniques were applied 
> to public policy decisions or medical diagnosis.   Without a linguistic 
> component that co-evolved to describe a taken action, one could be left with 
> robot savants that outperformed humans on crucial tasks and no one, including 
> the robot, would have any idea why.
>
> Sent from my iPhone
>
>
> On Mar 13, 2016, at 8:01 AM, Roger Critchlow <[email protected]> <[email protected]> 
> wrote:
>
> I've been watching parts of the match between Lee Sedol and Alpha Go on the 
> youtube deepmind channel.  It's quite good, they start off with a discussion 
> of the previous game, give running commentary during the game, and audibly 
> gasp when the progress of the game shocks them.  The post match press 
> conferences are not to be missed, either.  It's a completely trump free zone.
>
> But you're looking at a full day's work for each game, 6 hours and 17 minutes 
> of video from last night's game which Lee Sedol won.  I was too tired to stay 
> up and watch so I tuned into youtube this morning and watched the endgame.
>
> Apparently I forwarded past the key move, #78, which a Chinese journalist, 
> quoting a Chinese commentator, called "a God's move".  Lee Sedol replied that 
> it was the only move he had at the time, that he had thought it would be 
> easier to make some profit, but it was quite difficult.
>
> So the same play is described as both creative genius and inevitable in the 
> space of a few sentences.  Glad to know that some things will never change.
>
> -- rec --
>
>
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> Web Design & Development
> Santa Fe, NMhttp://cirrillian.com
> 281-989-6272 (cell)
> Member Design Corps of Santa Fe
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