69 Open source projects that are alternatives of or similar to ppo-pytorch

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Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

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).

Deep Reinforcement Learning by using Proximal Policy Optimization and Random Network Distillation in Tensorflow 2 and Pytorch with some explanation

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

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

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

Reinforcement learning tutorials

Deep Reinforcement Learning Algorithms implemented with Tensorflow 2.3

Master classic RL, deep RL, distributional RL, inverse RL, and more using OpenAI Gym and TensorFlow with extensive Math

This is the official implementation of Multi-Agent PPO.

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

Live Trading. Please star.

Reinforcement learning models in ViZDoom environment

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

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

Curiosity-driven Exploration by Self-supervised Prediction for Street Fighter III Third Strike

Reason8.ai PyTorch solution for NIPS RL 2017 challenge

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

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".

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

An elegant PyTorch deep reinforcement learning library.

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

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

Lightweight deep RL Libraray for continuous control.

Trading Environment(OpenAI Gym) + PPO(TensorForce)

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

ROS 2 enabled Machine Learning algorithms

LaTeX template, Outstanding papers of last years and some useful books about MATLAB

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

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

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

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

TD-Regularized Actor-Critic Methods

Implementing reinforcement-learning algorithms for pysc2 -environment

☔ Deep RL agents with PyTorch☔

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

A pytorch tutorial for DRL(Deep Reinforcement Learning)

Provide full reinforcement learning benchmark on mujoco environments, including ddpg, sac, td3, pg, a2c, ppo, library

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

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

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

Modularized Implementation of Deep RL Algorithms in PyTorch

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)

juliareinforcementlearning.org/

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

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

A PyTorch library for building deep reinforcement learning agents.

Repo for the Deep Reinforcement Learning Nanodegree program

🔥🌟《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!

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

RL agent to play μRTS with Stable-Baselines3 and PyTorch

a unified environment for supervised learning and reinforcement learning in the context of quantitative trading

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.