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Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Antonin RAFFIN <antonin.raffin@ensta.org>

Author: araffin

docs/guide/config.md

@@ -2,7 +2,7 @@
 
 # Configuration
 
-## Hyperparameter yaml syntax
+## Hyperparameter YAML syntax
 
 The syntax used in `hyperparameters/algo_name.yml` for setting
 hyperparameters (likewise the syntax to [overwrite

docs/guide/install.md

@@ -4,7 +4,7 @@
 
 ## Prerequisites
 
-RL Zoo requires python 3.8+ and PyTorch >= 1.13
+RL Zoo requires Python 3.10+ and PyTorch >= 2.3
 
 ## Minimal Installation
 
@@ -36,8 +36,8 @@ additionally to download the ROMs
 :::
 
 ```bash
-      apt-get install swig cmake ffmpeg
-      pip install -r requirements.txt
+apt-get install swig cmake ffmpeg
+pip install -r requirements.txt
 pip install -e .[plots,tests]
 ```
 

docs/guide/integrations.md

@@ -4,15 +4,15 @@
 
 ## Huggingface Hub Integration
 
-List and videos of trained agents can be found on our Huggingface page: <https://huggingface.co/sb3>
+Lists and videos of trained agents can be found on our Huggingface page: <https://huggingface.co/sb3>
 
 Upload model to hub (same syntax as for `enjoy.py`):
 
 ```
 python -m rl_zoo3.push_to_hub --algo ppo --env CartPole-v1 -f logs/ -orga sb3 -m "Initial commit"
 ```
 
-you can choose custom `repo-name` (default: `{algo}-{env_id}`) by
+You can choose custom `repo-name` (default: `{algo}-{env_id}`) by
 passing a `--repo-name` argument.
 
 Download model from hub:
@@ -35,5 +35,5 @@ python train.py --algo ppo --env CartPole-v1 --track --wandb-project-name sb3
 yields a tracked experiment at this
 [URL](https://wandb.ai/openrlbenchmark/sb3/runs/1b65ldmh).
 
-To add a tag to the run, (e.g. `optimized`), use the argument
+To add a tag to the run (e.g. `optimized`), use the argument
 `--wandb-tags optimized`.

docs/guide/plot.md

@@ -59,4 +59,4 @@ each environment.
 :::
 
 Remark: plotting with the `--rliable` option is usually slow as
-confidence interval need to be computed using bootstrap sampling.
+confidence intervals need to be computed using bootstrap sampling.

docs/guide/train.md

@@ -8,7 +8,7 @@ The hyperparameters for each environment are defined in
 `hyperparameters/algo_name.yml`.
 
 :::{note}
-Once RL Zoo3 is install, you can do `python -m rl_zoo3.train` from any folder, it is equivalent to `python train.py`
+Once RL Zoo3 is installed, you can run `python -m rl_zoo3.train` from any folder, which is equivalent to `python train.py`.
 :::
 
 If the environment exists in this file, then you can train an agent using: