322 Open source projects that are alternatives of or similar to Pytorch Trpo

A collection of materials to help you learn about deep learning

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

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

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MuZero

StarCraft II - pysc2 Deep Reinforcement Learning Examples

Deep Reinforcement Learning Notes

Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.

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TensorFlow implementation of Deep Reinforcement Learning papers

An evolving guide to learning Deep Learning effectively.

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

Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving

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

Rainbow: Combining Improvements in Deep Reinforcement Learning

Deep Reinforcement Learning based Trading Agent for Bitcoin

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

Code repository for the Animal AI Olympics competition

Notes and comments about Deep Reinforcement Learning papers

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

Train robotic agents to learn to plan pushing and grasping actions for manipulation with deep reinforcement learning.

Code for reproducing experiments in Model-Based Active Exploration, ICML 2019

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

Deep Reinforcement Learning (DRL) agents applied to medical images

A3C LSTM Atari with Pytorch plus A3G design

Reproducing MuJoCo benchmarks in a modern, commercial game /physics engine (Unity + PhysX).

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Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...

Source codes for the book "Reinforcement Learning: Theory and Python Implementation"

Playing Atari games with TensorFlow implementation of Asynchronous Deep Q-Learning

(⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.

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

Python library for Reinforcement Learning.

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

A PyTorch library for building deep reinforcement learning agents.

My Solutions of Assignments of CS234: Reinforcement Learning Winter 2019

Pytorch code for ICLR-20 Paper "Learning to Explore using Active Neural SLAM"

Implementation of the Deep Q-learning algorithm to solve MDPs

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

Resources, papers, tutorials

Repo for the Deep Reinforcement Learning Nanodegree program

For deep RL and the future of AI.

Seq2seq chatbot with attention and anti-language model to suppress generic response, option for further improve by deep reinforcement learning.

My Solution to Assignments of CS234

TensorFlow2 Reinforcement Learning

Using deep reinforcement learning to tackle the game 2048.

Play Google Chrome's T-rex game with TensorFlow

Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:

A High Level Python Deep Reinforcement Learning library. Great for beginners, prototyping and quickly comparing algorithms

Teach a Quadcopter How to Fly!

🎮 Advanced Deep Learning and Reinforcement Learning at UCL & DeepMind | YouTube videos 👉

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

🤖 Implements of Reinforcement Learning algorithms.

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Notes on Deep Reinforcement Learning for Natural Language Processing papers