A Deep Dive into Monte Carlo Tree Search

made by brilee, submitted by porterjamesj
Brian gives a deep explanation of how Monte Carlo Tree Search (a key technique for game AIs) works. He implemented the AlphaGo paper from scratch, so he should know!

Understanding the AUROC metric

made by brilee, submitted by porterjamesj
An explanation of metrics for comparing statistical classifiers, and why the most common one, AUROC, is so commonly used.

MuGo

made by brilee, submitted by davidbalbert
A minimal Go AI modeled on AlphaGo. It became the basis of Minigo (https://github.com/tensorflow/minigo), which is maintained by the Tensorflow team.