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21 lines
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Plaintext
21 lines
1.5 KiB
Plaintext
# Introduction:
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<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit13/thumbnail.png" alt="Unit bonus 4 thumbnail"/>
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Welcome to this bonus unit, where you will **train a robot agent to complete a mini-game level using imitation learning.**
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At the end of the unit, **you will have a trained agent capable of solving the level as in the video**:
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<video src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit13/onnx_inference_test.mp4" type="video/mp4" controls autoplay loop mute />
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## Objectives:
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- Learn how to use imitation learning with Godot RL Agents by training an agent to complete a mini-game environment using human-recorded expert demonstrations.
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## Prerequisites and requirements:
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- It is recommended that you complete the previous chapter ([Godot RL Agents](https://huggingface.co/learn/deep-rl-course/unitbonus3/godotrl)) before starting this tutorial,
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- Some familiarity with Godot is recommended, although completing the tutorial does not require any gdscript coding knowledge,
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- Godot with .NET support (tested to work with [4.3.dev5 .NET](https://godotengine.org/article/dev-snapshot-godot-4-3-dev-5/), may work with newer versions too),
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- Godot RL Agents (you can use `pip install godot-rl` in the venv/conda env),
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- [Imitation library](train-our-robot.mdx),
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- Time: ~1-2 hours to complete the project and training. It can be outside of this range depending on the hardware used. |