nfragakis / DDPG-Reinforcement-Learning-Implementation

Train a Quadcopter to land from elevated position using a Deep Deterministic Policy Gradients Algorithm

Content: Deep Reinforcement Learning

Project: Training a Quadcopter through DDPG Algorithm

Install

This project requires Python 2.7 and the following Python libraries installed:

• NumPy
• Pandas
• matplotlib
• Keras
• Math

You will also need to have software installed to run and execute a Jupyter Notebook

Run

In a terminal or command window, navigate to the top-level project directory customer_segments/ (that contains this README) and run one of the following commands:

ipython notebook Quadcopter Project.ipynb

or

jupyter notebook Quadcopter Project.ipynb

This will open the Jupyter Notebook software and project file in your browser.

Project

Implement a Deep Deterministic Policy Gradients Algorithm to train a quadcopter (quadrotor helicopter) to land safely from an elevated starting position. Utilizing Keras to build out an Actor-Critic Neural Network model to perform policy and value updates with experiences sampled form a replay buffer.