I have trained neural networks for the Greek backgammon variants plakoto
and fevga. It seems like neural networks can capture much of the
complexity of these variants even with few expert features.
You can download a program that plays these variants from my webpage:
http://csse.uom.gr/~nikpapa/software.html
For now, there is no help, but if you are familiar with gnubg and the
rules of the games, you shouldn't have any problems :)
You can also see the paper describing the training process in the
publications section.
Cheers,
Nikos Papahristou
On 28/6/2011 23:17, Joseph Heled wrote:
A far more interesting and difficult task would be to go for one of
the other variants In my family they used to play machboosa
(surrounded), which is the same as the Greek Plakoto, which I find
strategically orders of magnitude harder. I can hardly tell if I make
sensible moves or not, as this is a game where you have to slow
yourself down usually not just a race to the line that is backgammon.
I even have doubts that a neural net can capture this complexity,
since most consequences are far ahead in the future - it is like
playing a backgame all the time, and we know how poor computer players
are at that, GNUBG especially.
-Joseph
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