Continuous control with deep reinforcement learning

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We adapt the ideas underlying the success of Deep Q-Learning to the continuous action domain. We present an actor-critic, model-free algorithm based on the deterministic policy gradient that can operate over continuous action spaces. Using the same learning algorithm, network architecture and hyper-parameters, our algorithm robustly solves more than 20 simulated physics tasks, including classic problems such as cartpole swing-up, dexterous manipulation, legged locomotion and car driving. Our algorithm is able to find policies whose performance is competitive with those found by a planning algorithm with full access to the dynamics of the domain and its derivatives. We further demonstrate that for many of the tasks the algorithm can learn policies end-to-end: directly from raw pixel inputs.

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Implemented a deep deterministic policy gradient with a neural network for the OpenAI gym pendulum environment.

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CS294 final project

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Fully Functional

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Using Keras and Deep Deterministic Policy Gradient to play TORCS

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Tensorflow + OpenAI Gym implementation of Deep Q-Network (DQN), Double DQN (DDQN), Dueling Network and Deep Deterministic Policy Gradient (DDPG)

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Fully Functional

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This project is an exercise in reinforcement learning as part of the Machine Learning Engineer Nanodegree from Udacity. The idea behind this project is to teach a simulated quadcopter how to perform some activities.

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Continuous control with deep reinforcement learning - Deep Deterministic Policy Gradient (DDPG) algorithm implemented in OpenAI Gym environments

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Implementation of some RL algorithms

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Two Deep Reinforcement Learning agents that collaborate so as to learn to play a game of tennis.

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My RL learning repository

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CS234 Project, Winter 2019

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Implementation of Deep Deterministic Policy Gradient learning algorithm

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A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)

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Models library for training one's computer

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github.com: /tegg89/mann

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MAGNet: Multi-agents control using Graph Neural Networks

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github.com: /J93T/TP4-DDPG

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Project for INF8225 TP4

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github.com: /madvn/DDPG

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Deep Deterministic Policy Gradients in TF r2.0

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Highly modularized implementation of popular deep RL algorithms by PyTorch

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Deep deterministic policy gradients + supervised learning for car steering control

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A deep reinforcement learning library in tensorflow

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A small demo of the DDPG algorithm using a toy env from the OpenAI gym, presented in the paper "Continuous control with deep reinforcement learning" by Lillicrap et al.

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Deep learning and reinforcement learning!

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Continuous Control with Deep Reinforcement Learning

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github.com: /Chujinjiao/DLND

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dlnd projects

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This tool is developed to scrape twitter data, process the data, and then create either an unsupervised network to identify interesting patterns or can be designed to specifically verify a concept or idea.

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Actor-Critic methods: Deep Deterministic Policy Gradients on Walker env

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github.com: /anita-hu/TF2-RL

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Reinforcement learning algorithms implemented for Tensorflow 2.0+ [DQN, DDPG, AE-DDPG]

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Implementation of Deep Deterministic Policy Gradients using TensorFlow and OpenAI Gym

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Using deep reinforcement learning (DDPG & A3C) to solve Acrobot

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DDPG implementation for collaboration and competition for a Tennis environment.

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This repository contains: 1. Unofficial code for paper "The Cross Entropy Method for Fast Policy Search" 2. Unofficial code for paper "Continuous control with deep reinforcement learning" 3. Unofficial code for paper "Deep Reinforcement Learning with Double Q-learning"

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Distributed Tensorflow Implementation of Continuous control with deep reinforcement learning (DDPG)

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My solution to Collaboration and Competition using MADDPG algorithm, Udacity 3rd project of Deep RL Nanodegree from the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"

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DDPG on OpenAI Gym Pendulum

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This is a baselines DDPG implementation with added Robotic Auxiliary Losses

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Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

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baseline DDPG implementation less than 400 lines

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A biologically inspired, hierarchical bipedal locomotion controller for robots, trained using deep reinforcement learning.

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github.com: /kushagra06/DDPG

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Deep Deterministic Policy Gradient (Deep RL algorithm)

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Reinforcement Learning

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Repository for Planar Bipedal walking robot in Gazebo environment using Deep Deterministic Policy Gradient(DDPG) using TensorFlow.

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An implementation of the Normalized Advantage Function Reinforcement Learning Algorithm with Prioritized Experience Replay

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github.com: /parilo/rl-server

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Reinforcement Learning Server

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This is a TensorFlow implementation of DeepMind's A Distributional Perspective on Reinforcement Learning.(C51-DDPG)

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Deep Reinforcement Learning Agent that solves a continuous control task using Deep Deterministic Policy Gradients (DDPG)

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Deep Reinforcement Learning Nanodegree project on continuous control, based on the DDPG algorithm.

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This repo is for policy gradient method

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"The Intern"--My code for RL applications at IIITA.

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github.com: /floodsung/DDPG

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Reimplementation of DDPG(Continuous Control with Deep Reinforcement Learning) based on OpenAI Gym + Tensorflow

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practice about reinforcement learning, including Q-learning, policy gradient, deterministic policy gradient and deep deterministic policy gradient

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Deep Reinforcement Learning for Keras.

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Repository for Planar Bipedal walking robot in Gazebo environment using Deep Deterministic Policy Gradient(DDPG) using TensorFlow.

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Deep Deterministic Policy Gradient (DDPG) implementation using Pytorch

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Tensorflow implementation of the DDPG algorithm

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Project with Udacity

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Two agents cooperating to avoid loosing the ball, using Deep Deterministic Policy Gradient in Unity environment

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github.com: /liuyuezhang/pyrl

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PyTorch deep reinforcement learning library focusing on reproducibility and readability.

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Reinforcement learning environments with musculoskeletal models

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Implementation of some common RL models in Tensorflow

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github.com: /pwasows/ddpg

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solving openai gym environments

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Examples of published reinforcement learning algorithms in recent literature implemented in TensorFlow

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[Unofficial] Udacity's How to Train a Quadcopter Best Practices

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Multi-Agent Deep Deterministic Policy Gradient applied in Unity Tennis environment

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Simple scripts concern about continuous action DQN agent for vrep simluating domain

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Framework for deep reinforcement learning.

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Deep Deterministic Policy Gradient (DDPG) implemented for the unity Reacher Environment

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github.com: /Dekki-Aero/DDPG

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Implimenting DDPG Algorithm in Tensorflow-2.0

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Helper for NeurIPS 2018 Challenge: AI for Prosthetics

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Reimplementation of DDPG(Continuous Control with Deep Reinforcement Learning) based on OpenAI Gym + Tensorflow

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github.com: /InSpaceAI/RL-Zoo

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Github: rmst/ddpg

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Implementation of Deep Deterministic Policy Gradients using TensorFlow and OpenAI Gym

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Udacity project for teaching a Quadcoptor how to fly.

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github.com: /shakedzy/gin

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Models library for training one's computer

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Solution

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Implementation of DDPG (Modified from the work of Patrick Emami) - Tensorflow (no TFLearn dependency), Ornstein Uhlenbeck noise function, reward discounting, works on discrete & continuous action spaces

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lis version 1 for private

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Github: TolgaOk/DPG

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This repository serves as the collaboration of practical project NST.

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Deep Deterministic Policy Gradient

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