From Newsgroup: rec.games.backgammon

Hi Ian,

Since this specific subject also strayd from the value of
cube ownership, I'll do the same with it by creating a new
thread and posting it also to RGB and Bgonline. My response
to you is below the quoted posts.

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*From:* MK <playbg-rgb@yahoo.com>
*Sent:* Wednesday, April 3, 2024 10:01:17 PM
*To:* Ian Shaw <Ian.Shaw@riverauto.co.uk>; GnuBg Bug <bug-gnubg@gnu.org> *Subject:* Re: Interesting question/experiment about value of cube ownership On 4/2/2024 5:13 AM, Ian Shaw wrote:

What would be your proposed structure for training a
cubeful bot? What gains and obstacles do you foresee.

I don't know what you mean by "structure". What I propose
is doing the same thing done training TD-Gammon v.1, i.e.
random self-play, but this time also cubeful and matchful,
i.e. random cube as well as checker decisions.

Apparently Tseauro still works at IBM with access to huge
CPU powers. Perhaps he can be put to shame for the damage
he caused to BG AI by what he did with TD-Gammon v.2 and
be urged to redeem himself.

In other forums, people talk about doing "XG rollouts on
Amazon's cloud servers", etc. Doing more biased rollouts
is plain stupid/illogical. Any such efforts would be put
to better use in training a new bot instead. The question
is who would volunteer to do it.

People like the Alpha-Zero team, etc. don't seem to want
to touch "gamblegammon" with a ten feet pole, possibly
because of the gambling nature of the game.

In the past, I have suggested in RGB that random rollout
feature can be added to GnuBG and results from trustable
users can be collected over time in a central database
to gradually create a bot that won't rely on concocted,
biased/inaccurate cube formulas and match equity tables.

Unfortunately the faithfuls are happy with their dogmas
and no better bots are likely in the near future... :(

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On 4/3/2024 11:44 PM, Ian Shaw wrote:

MK: What I PROPOSE is doing the same thing done training
TD-Gammon v.1, I.E. random self-play, but this time also
cubeful and MATCHFUL, i.e. random cube as well as checker
decisions.

As I remember it (though it's many years since I read the
research), the self-play wasn't accomplished by picking
random moves. It was the initial network weights that were
random. The move picked was the best-ranked move of all
the evaluated moves. This is a calculation, not a random
selection.

How do you propose to rank double vs no double, and take
vs pass?

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I didn't say the selection was random. The self-play moves
were random. There were no "calculations" either. Moves were
compared and better performing ones rose up in rank. It was
kind of a "bubble sorting" of large numbers of statistical
data. I remember that Tom Keith had used the expression
"percolating up" in describing how he trained a Hypergammon
bot through cubeless random self-play. It's the only way,
(using "empirical data and scientific method"), to train a
"non-human-biased" BG bot, (at least as best as technically,
minimally as possible).

To answer your last question, just like checker decisions,
cube decisions to double, take, pass, etc. would be random
also and the "correct" cube decisions would "bubble up" the
same way. It will take huge amounts of computing power and
time, but nowadays we have both.

For "matchful" play, checker and/or cube decisions based on
match score need to be random as well, even if that requires
exponentially more computing power and time. Again, we have
both. It's just a matter of whether we want to do it. We can
distribute the task and/or spread it over time to let the
empirical, statistical data trickle in and accumulate.

Perhaps other people more knowledgeable in bot training can
suggest ways to go about it in more technical details.

MK
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