There must be some bug in your implementation. The best neural network that I have trained for Palamedes (including expert features) reaches 0.603 ppg against pubeval. I will be very much surprised if I see anything scoring above 0.75.
I am also curious about the performance of gnubg against pubeval. I would have done it myself if there was an easy way to get gnubg's cubeless evaluations from any backgammon position. Nikos On Tue, Jan 17, 2012 at 7:28 AM, Mark Higgins <[email protected]> wrote: > How does gnubg perform against the pubeval benchmark in cubeless play? > > I ask because I'm playing around with a backgammon network and have got > one that wins 83% of games and +0.945ppg against pubeval (10k cubeless > games). This is a single 80-hidden-node network with outputs for prob of > win, prob of gammon win, and prob of gammon loss; and just the original > Tesauro inputs. 0-ply. > > But in the TD-Gammon scholarpedia article it says that TD-Gammon 2.1 in > 1-ply mode wins only +0.596ppg against pubeval. (I think 1-ply here means > the gnubg 0-ply.) > > http://www.scholarpedia.org/article/Td-gammon > > That seems really low compared to my result, since I'm pretty sure 2.1 had > gammon outputs and also extra customized inputs. > > So I'm wondering if I'm interpreting this correctly, or if I have an > incorrectly-setup version of pubeval, or something like that. > > > _______________________________________________ > Bug-gnubg mailing list > [email protected] > https://lists.gnu.org/mailman/listinfo/bug-gnubg >
_______________________________________________ Bug-gnubg mailing list [email protected] https://lists.gnu.org/mailman/listinfo/bug-gnubg
