A3c continuousA continuous action space version of A3C LSTM in pytorch plus A3G design
RlcycleA library for ready-made reinforcement learning agents and reusable components for neat prototyping
Tensorflow RlImplementations of deep RL papers and random experimentation
MinimalrlImplementations of basic RL algorithms with minimal lines of codes! (pytorch based)
MachinReinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
Baby A3cA high-performance Atari A3C agent in 180 lines of PyTorch
Reinforcementlearning AtarigamePytorch 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
A3c PytorchPyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch
Easy Rl强化学习中文教程,在线阅读地址:https://datawhalechina.github.io/easy-rl/
Deep Reinforcement Learning With PytorchPyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Torch AcRecurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO
Policy Gradient MethodsImplementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
Pytorch A3cPyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".
A3cMXNET + OpenAI Gym implementation of A3C from "Asynchronous Methods for Deep Reinforcement Learning"
Slm LabModular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
BomboraMy experimentations with Reinforcement Learning in Pytorch
TensorlayerDeep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
BtgymScalable, event-driven, deep-learning-friendly backtesting library
Pytorch RlDeep Reinforcement Learning with pytorch & visdom
Reinforcement learning tutorial with demoReinforcement 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..
Deep Rl KerasKeras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)
Pytorch A3cSimple A3C implementation with pytorch + multiprocessing
Ai BlogAccompanying repository for Let's make a DQN / A3C series.
Rl4jDeep Reinforcement Learning for the JVM (Deep-Q, A3C)
Rl Starter FilesRL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code
Deeprl Tensorflow2🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Pysc2 AgentsThis is a simple implementation of DeepMind's PySC2 RL agents.
pysc2-rl-agentsStarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)
Deep-Reinforcement-Learning-NotebooksThis Repository contains a series of google colab notebooks which I created to help people dive into deep reinforcement learning.This notebooks contain both theory and implementation of different algorithms.
a3cPyTorch implementation of "Asynchronous advantage actor-critic"
tf-a3c-gpuTensorflow implementation of A3C algorithm
Master-ThesisDeep Reinforcement Learning in Autonomous Driving: the A3C algorithm used to make a car learn to drive in TORCS; Python 3.5, Tensorflow, tensorboard, numpy, gym-torcs, ubuntu, latex
pytorch-noreward-rlpytorch implementation of Curiosity-driven Exploration by Self-supervised Prediction
cups-rlCustomisable Unified Physical Simulations (CUPS) for Reinforcement Learning. Experiments run on the ai2thor environment (http://ai2thor.allenai.org/) e.g. using A3C, RainbowDQN and A3C_GA (Gated Attention multi-modal fusion) for Task-Oriented Language Grounding (tasks specified by natural language instructions) e.g. "Pick up the Cup or else"
deep rl acrobotTensorFlow A2C to solve Acrobot, with synchronized parallel environments
yarllCombining deep learning and reinforcement learning.