TianshouAn elegant PyTorch deep reinforcement learning library.
MultihopkgMulti-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout
Deep AlgotradingA resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
A2cA Clearer and Simpler Synchronous Advantage Actor Critic (A2C) Implementation in TensorFlow
Show Adapt And TellCode for "Show, Adapt and Tell: Adversarial Training of Cross-domain Image Captioner" in ICCV 2017
Policy GradientMinimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras
Mlds2018springMachine Learning and having it Deep and Structured (MLDS) in 2018 spring
Pytorch RlTutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
Easy Rl强化学习中文教程,在线阅读地址:https://datawhalechina.github.io/easy-rl/
TorchrlHighly Modular and Scalable Reinforcement Learning
Deep Reinforcement Learning With PytorchPyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Deeprl algorithmsDeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)
Codegan[Deprecated] Source Code Generation using Sequence Generative Adversarial Networks
Parl SampleDeep reinforcement learning using baidu PARL(maze,flappy bird and so on)
Slm LabModular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".
BtgymScalable, event-driven, deep-learning-friendly backtesting library
Rlseq2seqDeep Reinforcement Learning For Sequence to Sequence Models
Pytorch RlPyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.
SeqganA simplified PyTorch implementation of "SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient." (Yu, Lantao, et al.)
DeerDEEp Reinforcement learning framework
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 RlThis repository contains model-free deep reinforcement learning algorithms implemented in Pytorch
Lagomlagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.
TrpoTrust Region Policy Optimization with TensorFlow and OpenAI Gym
Ppo PytorchMinimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch
Openai labAn experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.
deep tradingThis project aims to select a supervised algorithm that can predict stock prices basing on historical data and use the predictor generated to form trading strategies.
policy-gradient-pongtensorflow implementation of Andrej Karpathy's blog about reinforcement learning. http://karpathy.github.io/2016/05/31/rl/
ADL2019Applied Deep Learning (2019 Spring) @ NTU
SeqGAN-PyTorchImplementation of Sequence Generative Adversarial Nets with Policy Gradient in PyTorch
Deep-rl-mxnetMxnet implementation of Deep Reinforcement Learning papers, such as DQN, PG, DDPG, PPO
Paddle-RLBooksPaddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.
td-regTD-Regularized Actor-Critic Methods
HandyRLHandyRL is a handy and simple framework based on Python and PyTorch for distributed reinforcement learning that is applicable to your own environments.
ExplorerExplorer is a PyTorch reinforcement learning framework for exploring new ideas.
connect4Solving board games like Connect4 using Deep Reinforcement Learning
imitation learningPyTorch implementation of some reinforcement learning algorithms: A2C, PPO, Behavioral Cloning from Observation (BCO), GAIL.
RLA set of RL experiments. Currently including: (1) the MDP rank experiment, based on policy gradient algorithm
LWDRLCLightweight deep RL Libraray for continuous control.
TAA-PGUsage of policy gradient reinforcement learning to solve portfolio optimization problems (Tactical Asset Allocation).
DRL in CVA course on Deep Reinforcement Learning in Computer Vision. Visit Website:
deep rl acrobotTensorFlow A2C to solve Acrobot, with synchronized parallel environments
rpgRanking Policy Gradient