I'm embarrassed to admit that I didn't even know of that rule when designing the program, but will certainly include it in the first major update. Meanwhile, the program does not consider the match score at all when evaluating whether to double or accept a double, whereas you may, so any advantage here is with the human player. As you've probably noticed by now, you were just unlucky in never getting the first roll. You are right about the difficulties in creating a master player. Backgammon is a marvelously subtle game which poses delightful challenges for the programmer.
Neural nets are probably the best approach in the long run.
I was surprised at first that my genetic model did as well as it did. However, after a few years practice I can now beat it most of the time, the stronger programs you mention have come along, and I've had time to think of several ways to improve the model, so it's about time to go back to the computer and cook up something better. Back to other backgammon programs . Back to the neural net backgammon programs . Back to Machine Learning in Games .