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Co-authored-by: Nathan Raw <nxr9266@g.rit.edu>
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Thomas Simonini
2023-02-21 22:07:59 +01:00
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units/en/unit8/conclusion-sf.mdx
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# Conclusion
That's all for today. Congrats on finishing this Unit and the tutorial!
That's all for today. Congrats on finishing this Unit and the tutorial! ⭐️
Now that you've successfully trained your Doom agent, why not try deathmatch? But remember, that's a much more complex level than the one you've just trained. **But it's a nice experiment, and I advise you to try it.**
Now that you've successfully trained your Doom agent, why not try deathmatch? Remember, that's a much more complex level than the one you've just trained, **but it's a nice experiment and I advise you to try it.**
If you do it, don't hesitate to share your model in the `#rl-i-made-this` channel in our [discord server](https://www.hf.co/join/discord).
This concludes the last unit. But we are not finished yet! 🤗 The following **bonus unit include some of the most interesting, advanced and cutting edge work in Deep Reinforcement Learning**.
This concludes the last unit, but we are not finished yet! 🤗 The following **bonus unit includes some of the most interesting, advanced and cutting edge work in Deep Reinforcement Learning**.
See you next time 🔥,

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units/en/unit8/introduction-sf.mdx
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In this second part of Unit 8, we'll get deeper into PPO optimization by using [Sample-Factory](https://samplefactory.dev/), an **asynchronous implementation of the PPO algorithm**, to train our agent playing [vizdoom](https://vizdoom.cs.put.edu.pl/) (an open source version of Doom).
During the notebook, **you'll train your agent to play Health Gathering level**, where our agent must collect health packs to avoid dying. And after that, you can **train your agent to play more complex versions of the levels, such as Deathmatch**.
In the notebook, **you'll train your agent to play the Health Gathering level**, where the agent must collect health packs to avoid dying. After that, you can **train your agent to play more complex levels, such as Deathmatch**.
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit10/environments.png" alt="Environment"/>

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units/en/unit8/introduction.mdx
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<figure>
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit10/environments.png" alt="Environment"/>
<figcaption>This is the environments you're going to use to train your agents: VizDoom environments</figcaption>
<figcaption>These are the environments you're going to use to train your agents: VizDoom environments</figcaption>
</figure>
Sounds exciting? Let's get started! 🚀