All,
Can anyone detail the design of the version of Mogo that beat the
professional? Or is there a web-page where at least the general approach
has been described? Is the information even public? I am not seeing the
the implementation details, just the overall design and general
strategies. However, if the implementation details are available, I
would love to see those as well.
I am confused around what Mogo used. Was it Monte Carlo only, UCT only,
Monte Carlo integrated with UCT, RAVE, etc? I have read through all of
the recent emails, and I have not been able to get a clear picture of
it's design. Mogo at one timed used Monte Carlo and UCT. I read an email
that the one that played the pro and won did not use UCT at all.
However, I thought the massive tests that Don did awhile back showed
that MC did not scale very well, but MC + UCT did.
And what language/platform is Mogo written in; C/C++, Java, Assembly,
PHP, etc.? And how did the language/platform choice impact the overall
efforts; speed them up, slow them down, complicate/ease creating the
parallelism on the super computer, etc.?
So, I am now confused precisely what method or methods were used and/or
integrated to produce the current scalable version of Mogo. I want to
know these details so I can at least get a better sense of what actually
occurred with the win. I don't care near as much about the hardware as I
do the software architecture and design.
Thank you,
Jim
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