841 Open source projects that are alternatives of or similar to Openai_lab

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..

Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学

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

Implementations of Reinforcement Learning Models in Tensorflow

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

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Minimal and Clean Reinforcement Learning Examples

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

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

This repository contains model-free deep reinforcement learning algorithms implemented 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)

Machine Learning and having it Deep and Structured (MLDS) in 2018 spring

Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]

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

DrQ: Data regularized Q

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

Repo for the Deep Reinforcement Learning Nanodegree program

A PyTorch library for building deep reinforcement learning agents.

Python library for Reinforcement Learning.

A3C LSTM Atari with Pytorch plus A3G design

Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow

Deep Reinforcement Learning For Sequence to Sequence Models

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

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

Deep Reinforcement Learning with pytorch & visdom

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

Paddle-RLBooks is a reinforcement learning code study guide based on pure PaddlePaddle.

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

Reason8.ai PyTorch solution for NIPS RL 2017 challenge

🤖 Implements 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!

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

PyTorch implementation of Hierarchical Actor Critic (HAC) for OpenAI gym environments

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

Lightweight deep RL Libraray for continuous control.

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

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

Minimal Monte Carlo Policy Gradient (REINFORCE) Algorithm Implementation in Keras

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

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

PyTorch implementation of Soft Actor-Critic (SAC)

Reinforcement Learning Algorithms

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

Scalable, event-driven, deep-learning-friendly backtesting library

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

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

A Clearer and Simpler Synchronous Advantage Actor Critic (A2C) Implementation in TensorFlow

TensorFlow A2C to solve Acrobot, with synchronized parallel environments

Multi-hop knowledge graph reasoning learned via policy gradient with reward shaping and action dropout

Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch

RLgraph: Modular computation graphs for deep reinforcement learning

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A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks

🖥️ CS446: Machine Learning in Spring 2018, University of Illinois at Urbana-Champaign

PyTorch implementations of Deep Reinforcement Learning algorithms (DQN, DDQN, A2C, VPG, TRPO, PPO, DDPG, TD3, SAC, SAC-AEA)

A reinforcement learning package for Julia