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Minor typo fix

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Andrey Voroshilov
2023-01-08 17:49:07 -08:00
parent 57ff8dba89
commit 0375bafec9
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units/en/unit3/hands-on.mdx
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@@ -137,7 +137,7 @@ To train an agent with RL-Baselines3-Zoo, we just need to do two things:
Here we see that:
- We use the `Atari Wrapper` that does the pre-processing (Frame reduction, grayscale, stack four frames frames),
- We use the `Atari Wrapper` that does the pre-processing (Frame reduction, grayscale, stack four frames),
- We use `CnnPolicy`, since we use Convolutional layers to process the frames.
- We train the model for 10 million `n_timesteps`.
- Memory (Experience Replay) size is 100000, i.e. the number of experience steps you saved to train again your agent with.