[Computer-go] Having an "estimated winrate" on the AGA pro game broadcasts

Álvaro Begué alvaro.begue at gmail.com
Wed Aug 31 17:35:06 PDT 2016


One could use a curve to map the MC winning rate to an actual winning
probability. It would take only thousands of games to learn such a curve
(as opposed to the 30 million games used to train the value network in
AlphaGo).

Álvaro.

On Wed, Aug 31, 2016 at 8:24 PM, Dan Schmidt <dfan at dfan.org> wrote:

> Hi Andrew, I enjoy the AGA broadcasts. I am mostly just an observer on
> this list rather than a go programming expert, but I do have a couple of
> things to say on this topic:
>
> 1. This is done all the time on chess broadcasts these days, and I hate
> it. I want to know what a strong player thinks is going on, not a computer.
> This is a bigger "problem" with chess than go because computers are now
> hugely stronger than the pro commentators, so the commentators become
> largely reduced to interpreting the computer output rather than getting
> across their own human ideas. Of course, a) this is less of an issue right
> now as go programs (except for AlphaGo, which is private) are not quite pro
> strength yet, b) top-level go games have less volatile swings than chess
> games, and perhaps most importantly c) my opinion may be in the minority.
>
> 2. Win rate is tough. Many programs can produce the win rate of their
> Monte Carlo Tree Search, but because that involves looking at lots of
> suboptimal moves on both sides, the reported win rate is closer to 50% than
> it should be. A reported win rate of 60% (in the futures explored by MCTS)
> probably means at least 80% in reality, assuming high-level play on both
> sides.
>
> Crazy Stone reports an evaluation (like B+3.5) and confidence though it
> cautions against taking it too seriously. My assumption is that it's
> something like the median result, and standard deviation, of all the MCTS
> playouts. I find this more useful than the win rate it provides.
>
> Dan
>
>
> On Wed, Aug 31, 2016 at 6:41 PM, Jackson, Andrew <andrew.jackson at usgo.org>
> wrote:
>
>> Hello all!  Long time lurker, first time poster:  I'm Andrew Jackson, i
>> volunteer w/ the AGA in a number of capacities.
>>
>> Most recently, i've been putting together live broadcasts of games --
>> professional games from CJK, and also games from AGA events [1]
>>
>> These broadcasts feature professional commentary to help amateurs
>> understand what's going on, but the number one question we get in the chat
>> during the broadcasts is invariably "who's winning?"  I was hoping
>> computer-go could provide some suggestions on how we might run the
>> game-in-progress through an engine to get an 'estimated winrate' -- or
>> better yet, a graph -- that could be overlaid in the corner of the screen.
>>
>> Which brings me to the computer-go mailing list :)  It seems like someone
>> on this mailing list would probably have some good ideas about how this
>> might be accomplished :)  What do you think?
>>
>>
>> Here are some more details:
>>
>> The game sgf is kept mirrored on KGS by a human transcriber w/ permission
>> from the KBA.
>>
>> The overlay for these broadcasts is already rendered as a local webserver
>> hosting a simple html shell holding the graphics; my thought was that this
>> server could easily make requests to another service somewhere.  That
>> service would be tracking the game and able to send back some json
>> describing the engine's view of the game, its confidence, etc.  We could
>> then plot with d3.js right on the overlay.
>>
>> The service would need to run somewhere else, as the computer streaming
>> the game is already using all the CPU for transcoding & pushing the video.
>>
>> Given general overview of the goal & constraints, I ask you:
>>
>>  - Does this sound plausible?
>>  - Any ideas for an engine that would be easy to hook this into?
>>  - Are bots capable of spectating games on KGS?
>>
>> Thanks in advance for any help you might provide!
>> -Andrew
>>
>>
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>
>
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