presentation on AlphaZero for AI seminar (http://ktiml.mff.cuni.cz/~bartak/ui_seminar/)
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Updated
Jan 6, 2018 - TeX
presentation on AlphaZero for AI seminar (http://ktiml.mff.cuni.cz/~bartak/ui_seminar/)
A simplified version of Shogi with the AI is trained by alpha-zero-type training method
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.
Omok using MCTS (UCT, PUCT)
Implementation of AlphaZero algorithm
Using self-play, MCTS, and a deep neural network to create a hearthstone ai player
A AlphaZero implementation for Othello 10x10 / Reversi using C++
AlphaZero for ultimate tic-tac-toe.
ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation
Reinforcement Learning applied to 3-Player Chinese Checkers
HybridAlpha - a mix between AlphaGo Zero and AlphaZero for multiple games
AlphaGo Zero implementation using Flux.jl
An implementation of the AlphaZero algorithm for adversarial games to be used with the machine learning framework of your choice
Visual representation of RTS game, supported by deep reinforcement learning algorithm Alpha Zero written in python.
This model implements the Alpha Zero paper on the game of Reversi/Orthello.
AlphaZero-like AI solution for playing Ultimate Tic-Tac-Toe in the browser
A collection of papers & notes in deep learning and database.
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