There are 6 repositories under a3c topic.
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
强化学习中文教程(蘑菇书🍄),在线阅读地址:https://datawhalechina.github.io/easy-rl/
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Minimal and Clean Reinforcement Learning Examples
Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)
PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
Asynchronous Advantage Actor-Critic (A3C) algorithm for Super Mario Bros
Deep Reinforcement Learning with pytorch & visdom
Reinforcement Learning Tutorial with Demo: DP (Policy and Value Iteration), Monte Carlo, TD Learning (SARSA, QLearning), Function Approximation, Policy Gradient, DQN, Imitation, Meta Learning, Papers, Courses, etc..
RL starter files in order to immediately train, visualize and evaluate an agent without writing any line of code
Asynchronous Methods for Deep Reinforcement Learning
🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Simple A3C implementation with pytorch + multiprocessing
A3C LSTM Atari with Pytorch plus A3G design
Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)
Reinforcement learning tutorials
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
This is a simple implementation of DeepMind's PySC2 RL agents.
A continuous action space version of A3C LSTM in pytorch plus A3G design
Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
Implementations of deep RL papers and random experimentation
Pytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games
Curiosity-driven Exploration by Self-supervised Prediction for Street Fighter III Third Strike
StarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
Combining deep learning and reinforcement learning.
Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO
DQN, DDDQN, A3C, PPO, Curiosity applied to the game DOOM
pytorch implementation of Curiosity-driven Exploration by Self-supervised Prediction