803 Open source projects that are alternatives of or similar to Autonomous Learning Library

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

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

Repo for the Deep Reinforcement Learning Nanodegree program

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.

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

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)

RLgraph: Modular computation graphs for deep reinforcement learning

Python library for Reinforcement Learning.

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.

Modularized Implementation of Deep RL Algorithms in PyTorch

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

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🤖 Implements of Reinforcement Learning algorithms.

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

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

🔥🌟《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!

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

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

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

Live Trading. Please star.

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

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

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

Lightweight deep RL Libraray for continuous control.

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

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

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

Mxnet implementation of Deep Reinforcement Learning papers, such as DQN, PG, DDPG, PPO

An elegant PyTorch deep reinforcement learning library.

Minimal Deep Q Learning (DQN & DDQN) implementations in Keras

juliareinforcementlearning.org/

A pytorch tutorial for DRL(Deep Reinforcement Learning)

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

Deep Reinforcement Learning with pytorch & visdom

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

Reason8.ai PyTorch solution for NIPS RL 2017 challenge

No description or website provided.

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

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

RAD: Reinforcement Learning with Augmented Data

Highly Modular and Scalable Reinforcement Learning

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

ROS 2 enabled Machine Learning algorithms

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.

Solving OpenAI Gym problems.

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

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).

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

Reinforcement learning tutorials

playing idealized trading games with deep reinforcement learning

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

Pytorch Implementation of RL algorithms

End to end motion planner using Deep Deterministic Policy Gradient (DDPG) in gazebo