Udacity Deep Reinforcement Learning Nanodegree. Second Project Implementation (Continuous Control).
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Updated
Dec 8, 2020 - Python
Udacity Deep Reinforcement Learning Nanodegree. Second Project Implementation (Continuous Control).
Tests SOTA algorithms using pendulum as baseline environment
A Deep Learning project which designs an agent that can fly a quad-copter, and then train it using a reinforcement learning algorithm DDPG
Torce self-driving
A DDPG agent that solves the Reacher Unity environment
BS diploma at MIPT DCAM
Teach a quadcopter how to fly using reinforcement learning!
Teach a Quadcopter How to Fly!
This repository contains my assignment solutions for the Deep Reinforcement Learning course (430.729_003) offered by Seoul National University (Spring 2020).
Implementation of the Deep Deterministic Policy Gradient (DDPG) using PyTorch
The pytorch implementation of ddpg
Fun with Reinforcement Learning in my spare time
Streamline your TensorFlow workflow.
Solve the Inverted Pendulum Control problem using Deep Deterministic Policy Gradient model
🦾 Utilizing a Deep Deterministic Policy Gradient algorithm to train robotic simulations in continuous action space
Udacity Deep Reinforcement Learning Nanodegree. Third Project Implementation (Collaboration and Competition).
Example DDPG implementation with ReLAx
A merge between OpenAI Baselines and Stable Baselines with increased focus on HER+DDPG and ease of use. Simply run the bash script to get started!
scalable multi-agent reinforcement learning
Deep Reinforcement Learning: Continuous Control. Solve the Unity ML-Agents Reacher Environment.
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