Welcome to the adventurous world of the Machine Learning Roguelike! This guide will take you through the thrilling journey of setting up and training agents within this unique game that harnesses the power of Machine Learning.
Objective
The primary goal of this project is to demonstrate practical applications of Machine Learning Agents in a real game environment. In this game, both the player and enemy entities are driven by Machine Learning models, making every encounter both challenging and exciting.
Prerequisites
Before diving into the setup, ensure you have the following:
- Unity 2017.2 or later
- A computer (Windows or Mac)
- The Tensorflow Sharp plugin
- Installed Python API
Usage Instructions
To get started with the Machine Learning Roguelike, follow these steps:
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Add the Tensorflow Sharp plugin to your Assets folder:
Add the Tensorflow Sharp plugin -
Refer to the setup guide for Tensorflow Sharp Support for additional setup instructions.
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To train the agents, ensure the Python API is installed. Follow this guide on installation.
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Add the python folder from the Machine Learning Agents repository to your project (outside the Assets folder).
Extra Materials
For those curious minds eager to explore more about this project:
- Read about the creation of this project in the Unity blog post.
- Check out the slides for more insights: Link.
- Watch the talk video for an in-depth understanding: Link.
Understanding the Code
The beauty of this game lies in integrating Machine Learning to control in-game entities. You can think of it as teaching a child how to play chess. Initially, the child knows nothing; you start by showing them how the pieces move and then guiding them through simple strategies. Over time, they become better by learning from their wins and losses, ultimately developing their own strategies. This is akin to how the ML Agents learn through various interactions in the game!
Troubleshooting
If you encounter challenges during setup or gameplay, here are a few ideas to help you out:
- Ensure all required software versions are installed correctly.
- Check the connections to the Tensorflow Sharp plugin and verify its presence in your Assets folder.
- If your agents aren’t learning, double-check the Python API installation and its path in your project.
- Consult the Machine Learning Agents wiki for additional troubleshooting tips.
For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.
Conclusion
Machine Learning Roguelike is not just a game; it’s a groundbreaking example of how Machine Learning can create rich and interactive experiences. Whether you are a developer looking to implement AI in gaming or just a curious gamer, this project offers a peek into the future of gaming technology.
At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.
