This repository implements the AlphaZero algorithm to train a Gomoku-playing AI entirely through self-play without human game data. It uses a deep neural network architecture combining a policy head (for move selection) and a value head (for board evaluation), trained via Monte Carlo Tree Search guided by the network during self-play. Supports PyTorch, TensorFlow, and Theano/Lasagne backends.