[computer-go] an idea... computer go program's rank vs time

[Nick Apperson]

ofcourse you are correct, P = 1.0 is just the random player.  Obviously the
ELO as a function of P is going to be continuous.  So, being really close to
P=1.0 will make for a player that is only very slightly better than random.

I think it is also interesting to consider a player worse than random.  Take
your 1 trial MC program and instead of playing only moves than win, play
only moves that lose.  My guess is that the skill difference between this
program and random would be greater than between random and 1 trial MC, but
I would be interested to see a trial of this.

On 1/25/07, Stuart A. Yeates <syeates at gmail.com> wrote:
>
>
>
> On 1/25/07, Don Dailey <drd at mit.edu> wrote:
> >
> >
> > I also had a difficult time producing a player that was less than
> > 200 ELO stronger than a random player.   Even a single play-out,
> > which seems hardly enough to discriminate between moves, is
> > enormously stronger than a random player.    It was pretty much
> > like this:
> >
> >    ASSUME computer is black
>
>
>  0.  with probably P, play a random move (using the same selection
> methodology as the random player)
>
>    1. play 1 random game.
> >
> >    2. If black wins,  play one of the first N black moves in the
> >       play-out  (all-as-first, for me it's some-as-first.)
> >
> >    3. If white wins, play one of the black move NOT in the play-out.
> >
> >    4. Crush a random player!
> >
>
>
> Surely by varying P, you can get a player arbitarily close to the random
> player?
>
> Or am I missing something?
>
> cheers
> stuart
>
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