Hi Timothy,
What it did was letting a bot play on FIBS against human players. I started
with 0 noise for about 10000 matches, then increased the noise to 0.007 for
another 10k matches, increased again etc. For each noise setting I could
estimate its actual strength on FIBS based on the match outcomes and the
accompanying opponents ratings, i.e. estimates were made using logistic
regression, not by analysing the matches with GNU backgammon.
For 0 ply, zero noise ('expert') it estimated about 2035; for 0.015 noise it
estimated 1825 etc.
What I meant with my remark is this: in my opinion, an intermediate player will
hoover around 1650 on FIBS, so a better noise level for GNU's 'intermediate'
will be 0.012. Similar, a beginner will hoover around 1400 on FIBS, so 0.034
would be a better setting for 'beginner'. A 1900 player on FIBS is IMO an
expert, so 0.010 noise is more suitable for the 'expert' preset, etc.
Bottom line is, GNU backgammon noise levels for the presets are too high,
particularly for intermediate/casual player/beginner.
On Sunday, 2 March 2014, 20:17, Timothy Y. Chow <tc...@alum.mit.edu> wrote:
On Sun, 2 Mar 2014, boomslang wrote:
>> I cannot give you Snowie error rates for the several settings, but I can
>> give you an estimated FIBS rating for various noise settings.
>[...]
>> Looking at the table, I would say that the noise settings for
>> intermediate, casual player and beginner are set too high.
>
>Thanks, boomslang! If I understand your comment, you're saying that if we
>were to record a bunch of matches and analyze them using, say, world-class
>settings, then the so-called "Intermediate" player would be assessed as
>being worse than "Intermediate" (and similarly for "Casual Player" and
>"Beginner")? But "Expert" and "Advanced" would (usually) get assessed as
>"Expert" and "Advanced" respectively?
>
>
>Tim
>
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