Simple reinforcement learning framework for selfplay experiments
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Updated
Apr 8, 2018 - Python
Simple reinforcement learning framework for selfplay experiments
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.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
A multi agent re-enforcement learning environment for many on many bot fights between space ships
A chess program based on Deep Mind's AlphaZero.
Using self-play, MCTS, and a deep neural network to create a hearthstone ai player
AlphaZero for ultimate tic-tac-toe.
Temporal difference learning for ultimate tic-tac-toe.
This is the implementation of paper Model Free Episodic Control
Implementation of Alpha Go Zero - Reinforcement Learning Project, COL870 @iit-delhi
Code repository for On the interaction between supervision and self-play in emergent communication (ICLR 2020)
An implementation of the AlphaZero algorithm for adversarial games to be used with the machine learning framework of your choice
Train a neural network to play 2048
The exact codes used by the team "liveinparis" at the kaggle football competition ranked 6th/1141
A Smart Agent using reinforcement learning with CNN + MCTS to learn to play Othello/Reversi
An asynchronous implementation of AlphaZero, a self-play reinforcement learning algorithm.
Implementation of TD Gammon algorithm by Gerald Tesauro at IBM's Thomas J. Watson Research Center in Python.
Multi-agent Self-Play Reinforcement Learning Library
A gym environment to train chatbots.
Using Value Iteration and Policy Iteration to discover the optimal solution for the strategic dice game PIG. Ultimately interested in whether the optimal solution can be reached through self-play alone.
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