Deep Reinforcement Learning in Unity

🤔 What is this project?

This project explores deep reinforcement learning (DRL) within Unity, focusing on training an agent to jump over obstacles. The agent receives positive rewards for successfully jumping over a block and negative rewards for touching the obstacle. With this project I am learning more about neural networks and how to develop a fully functional DRL solution to teach the agent optimal behavior through trial and error.

✨ Dependency

This project depends on my Neural Network from scratch project, which I just copied into Unity.

❗Current Status

The project is still under development, and the agent does not yet behave perfectly. Further training and optimization are needed to improve its performance and stability.

🛠️ Features

• Unity Integration: The project is made entirely in Unity.
• Reward System: Positive rewards for successful jumps and negative penalties for hitting obstacles.
• Deep Reinforcement Learning: Utilizes DRL to enable the agent to learn autonomously through feedback from its environment.

📊 Performance and Challenges

Initial training is yielding mixed results, with the agent sometimes failing to jump over the obstacles.

🏗️ Get Started

1. Clone the repository.
2. Open the project in Unity.
3. Run the game to watch the agent in action and adjust training settings as needed.