Top 68 ppo open source projects

An elegant PyTorch deep reinforcement learning library.

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

Modularized Implementation of Deep RL Algorithms in PyTorch

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).

🔥🌟《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!

31 projects in the framework of Deep Reinforcement Learning algorithms: Q-learning, DQN, PPO, DDPG, TD3, SAC, A2C and others. Each project is provided with a detailed training log.

Implementations of basic RL algorithms with minimal lines of codes! (pytorch based)

Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...

Trading Environment(OpenAI Gym) + PPO(TensorForce)

Implementation of the paper "Towards Optimally Decentralized Multi-Robot Collision Avoidance via Deep Reinforcement Learning"

ROS 2 enabled Machine Learning algorithms

Reinforcement learning models in ViZDoom environment

强化学习中文教程，在线阅读地址：https://datawhalechina.github.io/easy-rl/

Tensorflow implementation of Generative Adversarial Imitation Learning(GAIL) with discrete action

PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....

DeepRL algorithms implementation easy for understanding and reading with Pytorch and Tensorflow 2(DQN, REINFORCE, VPG, A2C, TRPO, PPO, DDPG, TD3, SAC)

Pytorch Implementation of Reinforcement Learning Algorithms ( Soft Actor Critic(SAC)/ DDPG / TD3 /DQN / A2C/ PPO / TRPO)

Reinforcement learning tutorials

Implementing reinforcement-learning algorithms for pysc2 -environment

Reason8.ai PyTorch solution for NIPS RL 2017 challenge

Recurrent and multi-process PyTorch implementation of deep reinforcement Actor-Critic algorithms A2C and PPO

This is the official implementation of Multi-Agent PPO.

Our NIPS 2017: Learning to Run source code

A custom MARL (multi-agent reinforcement learning) environment where multiple agents trade against one another (self-play) in a zero-sum continuous double auction. Ray [RLlib] is used for training.

Modular Deep Reinforcement Learning framework in PyTorch. Companion library of the book "Foundations of Deep Reinforcement Learning".

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

Contains high quality implementations of Deep Reinforcement Learning algorithms written in PyTorch

PyTorch implementation of Deep Reinforcement Learning: Policy Gradient methods (TRPO, PPO, A2C) and Generative Adversarial Imitation Learning (GAIL). Fast Fisher vector product TRPO.

Proximal Policy Optimization (PPO) algorithm for Super Mario Bros

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

Lightweight, efficient and stable implementations of deep reinforcement learning algorithms using PyTorch.

Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020. Please star.

A PyTorch library for building deep reinforcement learning agents.

This repository contains most of pytorch implementation based classic deep reinforcement learning algorithms, including - DQN, DDQN, Dueling Network, DDPG, SAC, A2C, PPO, TRPO. (More algorithms are still in progress)

Repo for the Deep Reinforcement Learning Nanodegree program

lagom: A PyTorch infrastructure for rapid prototyping of reinforcement learning algorithms.

PyTorch C++ Reinforcement Learning

RL starter files in order to immediatly train, visualize and evaluate an agent without writing any line of code

Minimal implementation of clipped objective Proximal Policy Optimization (PPO) in PyTorch

🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2

Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning

Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch

RLgraph: Modular computation graphs for deep reinforcement learning

RAD: Reinforcement Learning with Augmented Data

Proximal Policy Optimization(PPO) with Intrinsic Curiosity Module(ICM)

This 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.

A pytorch tutorial for DRL(Deep Reinforcement Learning)

A graphical interface for reinforcement learning and gym-based environments. Integrates tensorboard and various configuration utilities for ease of usage.

xingtian is a componentized library for the development and verification of reinforcement learning algorithms

Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG, SAC, PPO, Primal-Dual DDPG]

juliareinforcementlearning.org/

RL agent to play μRTS with Stable-Baselines3 and PyTorch

Scalable and Elastic Deep Reinforcement Learning Using PyTorch. Please star. 🔥

TD3, SAC, IQN, Rainbow, PPO, Ape-X and etc. in TF1.x

TD-Regularized Actor-Critic Methods

Deep Reinforcement Learning Algorithms implemented with Tensorflow 2.3

Explorer is a PyTorch reinforcement learning framework for exploring new ideas.

No description or website provided.

PyTorch implementation of some reinforcement learning algorithms: A2C, PPO, Behavioral Cloning from Observation (BCO), GAIL.