I have three computers that can do approximately 250,000 static evaluations / second each: I am happy to help in any way I can
Turker Eflanli On Mon, Oct 19, 2020 at 2:29 PM Øystein Schønning-Johansen < [email protected]> wrote: > On Mon, Oct 19, 2020 at 7:52 PM Joseph Heled <[email protected]> wrote: > >> I can comment on that: my experience from 20 years ago was that at some >> stage adding positions started to hurt the net performance. It is always a >> balancing act between getting the common/regular positions right and >> getting the edge cases right. I think that whatever you do you might want >> to start fresh and see how my "method" (as you outlined above) can be >> improved. >> > > Yes, I think I remember that you have mentioned that before. The reasoning > behind it might be due to the size (hence capacity) of the neural network. > Maybe, with a bigger and deeper neural network, and modern training > algorithms, a bigger training set can be used and still get better > performance. As you say, there is a sweet spot between getting the common > positions right, and then getting the edge cases right. > > Yes, the outlined method is (of course) Joseph's idea. In my view, he is > the best backgammon neural network trainer. Maybe I should start this > process on my own, and gain some experience before involving a community > with effort. It will be really unfortunate if we waste resources on a > braindead idea. > > How can the outlined idea be improved? Before I get into that, I think I > need some experience, but maybe see if there's some special kind of > positions that's over or under represented in the set, and then > automagically (in some way) detect these? > > -Øystein >
