Reversion to the mean, and a new method

So my current neural network I'm training, Larry, had previously increased his effectiveness to 90% against the SRP. Unfortunately, a few more dozen rounds decreased his effectiveness to the point that reverted to an 80% rating. That's unfortunate. On a lark, I started a new model on the side. This one was trained entirely by … Continue reading Reversion to the mean, and a new method


Dramatic improvements

As I wrote previously, I had run into the limit of how much my neural networks could improve by playing against purely random opponents (or even random opponents with shortcuts, such as always taking winning moves if available) because the signal to noise ratio of those players was simply too low. If a Neural Network … Continue reading Dramatic improvements