798 Open source projects that are alternatives of or similar to Pytorch Rl

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

Minimal and Clean Reinforcement Learning Examples

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

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

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

Python library for Reinforcement Learning.

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

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

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

Implementations of deep RL papers and random experimentation

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)

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

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

A3C LSTM Atari with Pytorch plus A3G design

PyTorch implementation of Asynchronous Advantage Actor Critic (A3C) from "Asynchronous Methods for Deep Reinforcement Learning".

Reinforcement 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..

🔥🌟《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!

ChainerRL is a deep reinforcement learning library built on top of Chainer.

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Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Reinforcement learning tutorials

Reason8.ai PyTorch solution for NIPS RL 2017 challenge

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ROS 2 enabled Machine Learning algorithms

Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

RLgraph: Modular computation graphs for deep reinforcement learning

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PyTorch implementation of Trust Region Policy Optimization

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.

An experimentation framework for Reinforcement Learning using OpenAI Gym, Tensorflow, and Keras.

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PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)

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

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

playing idealized trading games with deep reinforcement learning

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).

A library for ready-made reinforcement learning agents and reusable components for neat prototyping

Python code, PDFs and resources for the series of posts on Reinforcement Learning which I published on my personal blog

Repo for the Deep Reinforcement Learning Nanodegree program

Keras Implementation of popular Deep RL Algorithms (A3C, DDQN, DDPG, Dueling DDQN)

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PyTorch implementation of Soft Actor-Critic (SAC)

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This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

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

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

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

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

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