Deep Reinforcement Learning Gym From Scratch

Overview

This project is a Python-based implementation of a Deep Reinforcement Learning (DRL) Gym, utilizing TensorFlow for neural network computations. It's designed to demonstrate the principles of Deep Q-Learning by training an AI agent to navigate a grid environment towards a specified goal.

Detailed Article

For a comprehensive, follow-along guide and theoretical background, refer to my Medium article: Develop Your First AI Agent: Deep Q-Learning.

Technologies Used

• Python 3.11.6 - The programming language used.
• TensorFlow 2.14.0 - An open-source machine learning library by Google that we’ll use to build and train our neural network.

Features

• Customizable grid-based environment.
• Deep Q-Learning implementation for efficient learning.
• Experience replay to enhance the learning process.
• Adjustable parameters for experimentation.

Contact

Name - Heston Vaughan
Email - [email protected]
Article Link: Develop Your First AI Agent: Deep Q-Learning