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Re: current development


From: Nikos Papachristou
Subject: Re: current development
Date: Thu, 5 Dec 2019 13:30:17 +0200

Hi everybody!

You can view my research publications on backgammon variants at my website: https://nikpapa.com , or alternatively you can download my PhD thesis from:
https://www.didaktorika.gr/eadd/handle/10442/43622?locale=en

My personal view on improving GNUBG: Why not try to "upgrade" your existing supervised learning approach? There have been lots of advances in optimization/regularization algorithms for neural networks in the past years and it might be less demanding that trying a new RL self-play approach from scratch.

Regarding expected results, I also believe that backgammon bots are very close to perfection and whatever improvements (from any approach) will be marginal.



On Thu, Dec 5, 2019 at 12:14 AM Joseph Heled <address@hidden> wrote:
A link to something? article? software? did they use alpha-like strategies?

-Joseph

On Thu, 5 Dec 2019 at 11:04, Philippe Michel <address@hidden> wrote:
On Wed, Dec 04, 2019 at 02:07:18PM -0500, Timothy Y. Chow wrote:

> Also, it's my impression that many people *don't* think this is even a
> worthwhile idea to pursue.  Backgammon is already "solved," is what they
> will say.  It's true that "AlphaGammon" will surely not crush existing
> bots in a series of (say) 11-point matches.  At most I would expect a
> slight advantage.  But to me, that is the wrong way to look at the issue.
> I would like to understand superbackgames for their own sake, even though
> they arise rarely in practice.  Furthermore, if we know that bots don't
> understand superbackgames, then the closer a position gets to being a
> superbackgame, the less we can trust the bot verdict.

I'm not sure how related it may be, but there is a group of Greek
academics that have published some articles on their work on a bot,
Palamedes, that plays backgammon but also variants that have different
rules and starting positions and lead to positions that would be very
uncommon in backgammon.




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