Connect4 reinforcement learning by AlphaGo Zero methods.
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Updated
Apr 5, 2021 - Python
Connect4 reinforcement learning by AlphaGo Zero methods.
AlphaZero implementation for Othello, Connect-Four and Tic-Tac-Toe based on "Mastering the game of Go without human knowledge" and "Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm" by DeepMind.
board games for your terminal!
Master Thesis project that provides a training framework for two player games. TicTacToe and Othello have already been implemented.
HybridAlpha - a mix between AlphaGo Zero and AlphaZero for multiple games
Connect 4 Game implemented using minimax alpha beta pruning algorithm
AI for the Connect 4 game
A multi-agent implementation of the game Connect-4 using MCTS, Minimax and Exptimax algorithms.
Connect 4 is a token game created with Python and module Numpy. Place 4 tokens in a row (vertically, horizontally, or diagonally) before your opponent wins. Single-player against Artificial Intelligence and multiplayer also available.
University project in the course ICT Seminar 3. Using Tsetlin Machine for Pattern Recognition in the game Connect Four.
AI for the game "Connect Four". Available on PyPI.
Connect-4 AI inspired by the AlphaZero paper that uses Monte-Carlo Tree Search, and a neural policy and value estimator neural network trained with samples generated from self play between previous iterations of the model.
Connect 4 AI using Monte Carlo Tree Search algorithm.
Connect Four game written in Pygame
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