All Projects → zhihanyang2022 → off-policy-continuous-control

zhihanyang2022 / off-policy-continuous-control

Licence: GPL-3.0 license
[DeepRL Workshop, NeurIPS-21] Recurrent Off-policy Baselines for Memory-based Continuous Control (RDPG, RTD3 and RSAC)

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to off-policy-continuous-control

Pytorch A2c Ppo Acktr Gail
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
Stars: ✭ 2,632 (+8975.86%)
Mutual labels:  continuous-control, actor-critic
Fruit-API
A Universal Deep Reinforcement Learning Framework
Stars: ✭ 61 (+110.34%)
Mutual labels:  actor-critic
Mlds2018spring
Machine Learning and having it Deep and Structured (MLDS) in 2018 spring
Stars: ✭ 124 (+327.59%)
Mutual labels:  actor-critic
Reinforcement Learning
Minimal and Clean Reinforcement Learning Examples
Stars: ✭ 2,863 (+9772.41%)
Mutual labels:  actor-critic
A2c
A Clearer and Simpler Synchronous Advantage Actor Critic (A2C) Implementation in TensorFlow
Stars: ✭ 169 (+482.76%)
Mutual labels:  actor-critic
Baby A3c
A high-performance Atari A3C agent in 180 lines of PyTorch
Stars: ✭ 144 (+396.55%)
Mutual labels:  actor-critic
Reinforcementlearning Atarigame
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
Stars: ✭ 118 (+306.9%)
Mutual labels:  actor-critic
motion-planner-reinforcement-learning
End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo
Stars: ✭ 99 (+241.38%)
Mutual labels:  continuous-control
jax-rl
JAX implementations of core Deep RL algorithms
Stars: ✭ 61 (+110.34%)
Mutual labels:  actor-critic
Pytorch Drl
PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.
Stars: ✭ 233 (+703.45%)
Mutual labels:  actor-critic
Hands On Intelligent Agents With Openai Gym
Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch
Stars: ✭ 189 (+551.72%)
Mutual labels:  actor-critic
Machine Learning Is All You Need
🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!
Stars: ✭ 173 (+496.55%)
Mutual labels:  actor-critic
reinforcement learning with Tensorflow
Minimal implementations of reinforcement learning algorithms by Tensorflow
Stars: ✭ 28 (-3.45%)
Mutual labels:  actor-critic
deeprl-continuous-control
Learning Continuous Control in Deep Reinforcement Learning
Stars: ✭ 14 (-51.72%)
Mutual labels:  continuous-control
Adeptrl
Reinforcement learning framework to accelerate research
Stars: ✭ 173 (+496.55%)
Mutual labels:  actor-critic
Pytorch Rl
Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]
Stars: ✭ 121 (+317.24%)
Mutual labels:  actor-critic
LWDRLC
Lightweight deep RL Libraray for continuous control.
Stars: ✭ 14 (-51.72%)
Mutual labels:  continuous-control
Master-Thesis
Deep 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
Stars: ✭ 33 (+13.79%)
Mutual labels:  actor-critic
char-rnnlm-tensorflow
Char RNN Language Model based on Tensorflow
Stars: ✭ 14 (-51.72%)
Mutual labels:  recurrent-neural-network
Deep-Reinforcement-Learning-With-Python
Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math
Stars: ✭ 222 (+665.52%)
Mutual labels:  actor-critic

Recurrent Off-policy Baselines for Memory-based Continuous Control

This repo is the official codebase of our following paper:

@article{yang2021recurrent,
  title={Recurrent Off-policy Baselines for Memory-based Continuous Control},
  author={Yang, Zhihan and Nguyen, Hai},
  journal={Deep RL Workshop, NeurIPS 2021},
  year={2021}
}

Paper summary: We implement and benchmark recurrent versions of DDPG, TD3 and SAC that uses full history.

This repo offers:

  • DDPG, TD3 and SAC (clean PyTorch implementation and benchmarked against stable-baselines3*)
  • Recurrent versions of DDPG, TD3 and SAC that use full history: RDPG, RTD3 and RSAC
  • Very easy to understand and use; see our exhaustive documentation: link

*The results of benchmarking can be found in issue "Performance check against SB3" in closed Issues.

For users:

  • Please feel free to ask a code question through Issues.
  • When cloning this repo, please consider using shallow clone as it is large due to a large number of commits.

News:

  • [2021/11/18] Noticed that I forgot to document dependencies in documentation. Added.

Paper link:

https://arxiv.org/pdf/2110.12628.pdf

Poster (click to open in new tab for better resolution):

poster

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].