There are 1 repository under ddpg-agent topic.
An attempt to detect and prevent DDoS attacks using reinforcement learning. The simulation was done using Mininet.
Reason8.ai PyTorch solution for NIPS RL 2017 challenge
Implementation of the DDPG algorithm for Optimal Finance Trading
Important Note fastrl version 2 is being developed at fastrl. Note the link in the readme
Implementation of DDPG+HER on gym robotics environment FetchReach-v1
Learning Continuous Control in Deep Reinforcement Learning
La combinaciĂłn más inteligente de Deep Q-Learning, PolĂticas de Gradiente, Actor-CrĂtico y DDPG utilizando PyTorch
Multi-Agent training using Deep Deterministic Policy Gradient Networks, Solving the Tennis Environment
Tennis Game play using Multi Agent DDPG - Deep Reinforcement Learning
The DDPG algorithm incorporates Actor-Critic Deep Learning Agent for solving continuous action reinforcement learning problems.
Deep Reinforcement learning based tumour localisation
Learning to play tennis from scratch with AlphaGo Zero style self-play using DDPG
Learn how to apply reinforcement learning methods to applications that involve multiple, interacting agents. These techniques are used in a variety of applications, such as the coordination of autonomous vehicles.
DDPG algorithm applied for the double-jointed arm that can move to target locations.
Create and train a double-jointed arm agent that is able to maintain its hand in contact with a moving target
Repo for the Deep Reinforcement Learning Nanodegree program
Teach a Quadcopter How to Fly!
Learning agents in oligopolies (Cournot / Stackelberg) Agent-based model
Implementation of Policy Gradient Methods for Continuous and Discrete Action Spaces
A model to control a double-jointed arm to reach target using Deep Deterministic Policy Gradients
Basic implementation of continuous control agents trained using deep reinforcement learning. Project 2 of Udacity Deep Reinforcement Learning NanoDegree.
Implementations of Rl algorithms ranging from Q-learning to Multi-Agent RL using DDPG in unity and gym environments.
The program uses the DDPG algorithm and tf_agents library to train an agent in a custom environment called "TargetSeeker"
Usage of Unity ML-Agents train two agents to play tennis
Reinforcement Learning Project using DDPG
Teach a quadcopter how to fly using reinforcement learning!