347 Open source projects that are alternatives of or similar to pytorch-noreward-rl

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

Minimal and Clean Reinforcement Learning Examples

Deep Reinforcement Learning with pytorch & visdom

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

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

PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch

Reinforcement Learning for Super Mario Bros using A3C on GPU

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

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

A3C LSTM Atari with Pytorch plus A3G design

StarCraft II / PySC2 Deep Reinforcement Learning Agents (A2C)

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

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..

A high-performance Atari A3C agent in 180 lines of PyTorch

TensorFlow A2C to solve Acrobot, with synchronized parallel environments

Combining deep learning and reinforcement learning.

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

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.

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

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

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

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

"Good Robot! Now Watch This!": Repurposing Reinforcement Learning for Task-to-Task Transfer; and “Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer

An artificial intelligence platform for the StarCraft II with large-scale distributed training and grand-master agents.

UAV Obstacle Avoidance using Deep Recurrent Reinforcement Learning with Temporal Attention

Reinforcement Learning algorithm's using google-colab

Minimal implementations of reinforcement learning algorithms by Tensorflow

"Learning Machine Learning" Course, Bogotá, Colombia 2019 #LML2019

JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"

Mario AI Ensemble

This is a practical resource that makes it easier to learn about and apply Practical Deep Reinforcement Learning (DRL) https://ibrahimsobh.github.io/Practical-DRL/

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning

SeqGAN but with more bells and whistles

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

No description or website provided.

A simple example of how to implement vector based DQN using PyTorch and a ML-Agents environment

A Universal Deep Reinforcement Learning Framework

Deep Reinforcement Learning Pong Agent, King Pong, he's the best

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

AI项目（强化学习、深度学习、计算机视觉、推荐系统、自然语言处理、机器导航、医学影像处理）

Deep Reinforcement Learning A3C Crypto Trading Bot

Automate swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to sell, buy, or hold the stocks to maximize the gain in asset value. The paper also acknowledges the need for a system that predicts the trend in stock value to work along with the reinforcement …

JAX implementations of core Deep RL algorithms

(AAAI 2018) Action Branching Architectures for Deep Reinforcement Learning

Ramudroid, autonomous solar-powered robot to clean roads, realtime object detection and webrtc based streaming

Using self-play, MCTS, and a deep neural network to create a hearthstone ai player

A course on Deep Reinforcement Learning in Computer Vision. Visit Website:

Research into controllers for 2d and 3d Active Ragdolls (using MujocoUnity+ml_agents)

Deep Reinforcement Learning (DQN) based Self Driving Car Control with Vehicle Simulator

Deep & Classical Reinforcement Learning + Machine Learning Examples in Python

Code and data for "Deep Reinforcement Learning of Marked Temporal Point Processes", NeurIPS 2018

A car soccer environment inspired by Rocket League for deep reinforcement learning experiments in an adversarial self-play setting.

Remove watermark automatically(Just can use for fixed position watermark till now). 自动水印消除算法的实现（目前只支持固定水印位置）。

3D RL Volleyball environment built on Unity ML-Agents

☔ Deep RL agents with PyTorch☔

Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch

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

Deep Reinforcement Learning for Fixed-Wing Flight Control with Deep Q-Network

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