Playing Go without Game Tree Search Using Convolutional Neural Networks

no code implementations • 2 Jul 2019 • Jeffrey Barratt, Chuanbo Pan

We introduce three structures and training methods that aim to create a strong Go player: non-rectangular convolutions, which will better learn the shapes on the board, supervised learning, training on a data set of 53, 000 professional games, and reinforcement learning, training on games played between different versions of the network.

Game of Go reinforcement-learning +1