Well, actually, 1 million 296 thousand to be exact.
Here is the short of it (with details at the end of post):
GNUbg ID: tm0TAQSabdsAAA:cAkFAAAAAAAA
1,296,000 trials, cubeful, 0-ply with maximum noise
9/8 9/7 = cubeful -0.299, cubeless -0.297
7/6 7/5 = cubeful -0.420 (-0.121), cubeless -0.421 (-0.124)
3/1 2/1 = cubeful -0.498 (-0.199), cubeless -0.496 (-0.199)
3/2 3/1 = cubeful -0.526 (-0.227), cubeless -0.525 (-0.227)
One striking detail is how the cubefull and cubeless
equities for moves and cubefull and cubeless equity
differences between moves become mostly identical,
(i.e. "cube skill" evaporates), after 1,296,000 trials...!
If you want to double-check it yourselves, it shouldn't
take more than 4-5 hours on an average desktop PC.
I realize that the decisions aren't completely random
and thus there is still a minimal amount of jackoffski
bias in there but with 1 million 296 thousand trials, I
hope you won't lower yourselves as much to deny that
the results are accurate and revealing enough, without
the capability of fully eliminating the jackoffski bias in
current bots (among which Noo-Bg is the only one that
even comes close to it as above).
Too bad that developers of Ex-Gee, Noo-BG, BG-bzzt,
etc. won't make the minimal effort to add the feature
to do random rollouts to their bots, which would allow
us to undeniably demonstrate what kinds of pieces of
shits their gamblegammon bots are. :(
Although not as stumped as Zimmer, Paul, Tim and
Stick, I'm still stumped how 9/8 9/7 could be better
than 7/6 7/5, in a very sad and lonely way... :( ... ;)
MK
================================================
1. Rollout 9/8 9/7 Eq.: -0.299
35.3 0.0 0.0 - 64.7 0.3 0.1 CL -0.297 CF -0.299
[ 0.0 1.5 0.0 - 0.0 0.0 0.0 CL 0.001 CF 0.001]
Full cubeful rollout with variance reduction
1296000 games, Mersenne Twister dice generator with seed 2655780272
Play: 0-ply cubeful, noise 1 (d)
Cube: 0-ply cubeful, noise 1 (d)
2. Rollout 7/6 7/5 Eq.: -0.420 (-0.121)
29.3 0.0 0.0 - 70.7 0.5 0.2 CL -0.421 CF -0.420
[ 0.0 0.8 0.0 - 0.0 0.0 0.0 CL 0.001 CF 0.001]
Full cubeful rollout with variance reduction
1296000 games, Mersenne Twister dice generator with seed 2655780272
Play: 0-ply cubeful, noise 1 (d)
Cube: 0-ply cubeful, noise 1 (d)
3. Rollout 3/1 2/1 Eq.: -0.498 (-0.199)
25.6 0.0 0.0 - 74.4 0.5 0.2 CL -0.496 CF -0.498
[ 0.0 0.2 0.0 - 0.0 0.0 0.0 CL 0.001 CF 0.001]
Full cubeful rollout with variance reduction
1296000 games, Mersenne Twister dice generator with seed 2655780272
Play: 0-ply cubeful, noise 1 (d)
Cube: 0-ply cubeful, noise 1 (d)
4. Rollout 3/2 3/1 Eq.: -0.526 (-0.227)
24.1 0.0 0.0 - 75.9 0.6 0.2 CL -0.525 CF -0.526
[ 0.0 3.3 0.0 - 0.0 0.0 0.0 CL 0.001 CF 0.001]
Full cubeful rollout with variance reduction
1296000 games, Mersenne Twister dice generator with seed 2655780272
Play: 0-ply cubeful, noise 1 (d)
Cube: 0-ply cubeful, noise 1 (d)
I have no idea what you're trying to prove with a 0 ply rollout and max noise. You might as well let my cat chose which plays to make. That setting from memory is basically a pure beginner.
On 5/18/2023 7:01 AM, Stick Rice wrote:
I have no idea what you're trying to prove
with a 0 ply rollout and max noise.
His theory is that the "strong" bot settings
introduce serious systematic errors,
which he's trying to avoid by using random
errors instead,
and using large numbers of trials to smooth
out the random errors.
In particular, he'd be happy to use your cat,
except that your cat isn't fast enough.
On Thursday, May 18, 2023 at 5:09:09 AM UTC-4, MK wrote:
1,296,000 trials, cubeful, 0-ply with maximum noise
9/8 9/7 = cubeful -0.299, cubeless -0.297
7/6 7/5 = cubeful -0.420 (-0.121), cubeless -0.421 (-0.124)
3/1 2/1 = cubeful -0.498 (-0.199), cubeless -0.496 (-0.199)
3/2 3/1 = cubeful -0.526 (-0.227), cubeless -0.525 (-0.227)
I have no idea what you're trying to prove
with a 0 ply rollout and max noise.
GNUbg ID: tm0TAQSabdsAAA:cAkFAAAAAAAA
1,296,000 trials, cubeful, 0-ply with maximum noise
9/8 9/7 = cubeful -0.299, cubeless -0.297
7/6 7/5 = cubeful -0.420 (-0.121), cubeless -0.421 (-0.124)
3/1 2/1 = cubeful -0.498 (-0.199), cubeless -0.496 (-0.199)
3/2 3/1 = cubeful -0.526 (-0.227), cubeless -0.525 (-0.227)
MK <mu...@compuplus.net> writes:
GNUbg ID: tm0TAQSabdsAAA:cAkFAAAAAAAA
1,296,000 trials, cubeful, 0-ply with maximum noise
9/8 9/7 = cubeful -0.299, cubeless -0.297
7/6 7/5 = cubeful -0.420 (-0.121), cubeless -0.421 (-0.124)
3/1 2/1 = cubeful -0.498 (-0.199), cubeless -0.496 (-0.199)
3/2 3/1 = cubeful -0.526 (-0.227), cubeless -0.525 (-0.227)
Yes, I am finally convinced. Convinced that 9/8 9/7
is the best move against a random player, provided
that I also continue randomly after this "best" move.
Unfortunately that does not even help me against the
average coffee house player.
But playing against GNU Backgammon set to maximum
noise is relaxing and comforting, even funny sometimes,
because one can check how solid one's own backgammon
fundamentals are in very weird positions.
All bots since TD-Gammon, (and perhaps some even
before it), were trained through random self-play. Do
you have any objections to that?
What I am doing is making the bot train itself through
random self-play for a single position. Do you have any
objections to this in principle?
The 9/8 9/7 in this example isn't the best move against
only a random player. It's the best move period.
There is no limitation that the play continues randomly after this
"best" move either. Provided that the bot goes through enough cubeful
random trials, it will find "the best move"
Unfortunately that does not even help me against the
average coffee house player.
Because you either refuse to understand or you are not
able to understand it.
MK <mu...@compuplus.net> writes:
What I am doing is making the bot train itself
through random self-play for a single position.
Do you have any objections to this in principle?
Yes, I do. You do not train the bot, you run the
bot. No parameters of the neural network
will have changed after your random rollout.
The 9/8 9/7 in this example isn't the best
move against only a random player. It's the
best move period.
If you say so.
But are you not the guy advocating adapting the
play based on the opponent (which I support)?
How does that go along with your claim that the
best move against a random player is also the
best move against any opponent?
There is no limitation that the play continues
randomly after this "best" move either. Provided
that the bot goes through enough cubeful
random trials, it will find "the best move"
It will gather results and statistics based on
random play, essentially worthless against
non-random opponents.
Unfortunately that does not even help me
against the average coffee house player.
Because you either refuse to understand or
you are not able to understand it.
Correct.
future bots should perpetually update their networks with all rollouts
and games they play.
MK <mu...@compuplus.net> writes:
future bots should perpetually update their
networks with all rollouts and games they play.
IIRC, (much) older versions of GNU
Backgammon allowed for this.
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