Mastering 2014 using Deep Reinforcement Learning without human knowledge.

I utilized the A3C (Asynchronous Advantage Actor-Critic) algorithm to train a Deep Q-Learning (DQN) model, specifically tailored to solve the Kungfu gym environment.

PyTorch implementation of Asynchronous (and Synchronous) Advantage Actor Critic

Implementation of some deep RL algorithms

This project allows to train reinforcement learning agents in pysc2 environments.

PyTorch-based reinforcement learning implementation of A3C and DQN algorithms for a 2-player Catan environment

Forked from ikostrikov's repo. Changes made to adapt to new software versions(as of Jan 2021), and run on Linux.

A3C BrickBreaker - Game with RL

强化学习之超级马里奥，异步优势行动者与评论家

train_Machine_learning_to_beat_breakout

Reinforcement Learning Competition

The pytorch implementation of a3c

This code implements an Asynchronous Advantage Actor-Critic (A3C) algorithm using PyTorch to train an agent to play the Atari game "Boxing"

Deep reinforcement learning experiments

My implementations of popular reinforcement learning methods based on other developers and research papers.

This repository contains high quality and tested implementation of Asynchronous Actor Critic Algorithm