Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+task_categories:
+- reinforcement-learning
+tags:
+- imitation_learning
+- gymnasium
+- agents
+pretty_name: Labyrinth 4x4 Dataset
+size_categories:
+- 1K<n<10K
+---
+
+# Labyrinth 5x5 Dataset
+
+This dataset is for the gymnasium-base environment [Labyrinth-v0](https://github.com/NathanGavenski/maze-gym).
+It contains `obs`, `actions`, `rewards`, `episodeed_starts` and `info` for each entry based on `100` train, `100` validation and `100` test different structures.
+
+## Dataset Details
+
+### Dataset Description
+
+The dataset consists of the shortest route for each Labyrinth structure over `100` different structures for `3` different splits (`train`, `validation` and `test`).
+Each entry cosists of:
+
+```{python}
+obs (str): path to the image of the observation.
+action (int): the action for that observation (0-4).
+reward (float): the reward for that observation.
+episode_starts (bool): whether that observation was the initial timestep for that path.
+info (str): the custom setting language to load that structure into the environment if needed.
+```
+
+The dataset has `4` different splits (`train`, `validation`, `test`, and `random`).
+The `train`, `validation` and `test` are `100` different structures for training, validating and testing, respectively.
+The `random` split is for imitation learning and offline inverse reinforcement learning methods that require random samples to start (i.e., BCO, IUPE, SAIL).
+
+### Usage
+Feel free to download all files from this dataset and use it as you please.
+If you are interested in using our PyTorch Dataset implementation, feel free to check the [IL Datasets](https://github.com/NathanGavenski/IL-Datasets/blob/main/src/imitation_datasets/dataset/dataset.py) project.
+There, we implement a base Dataset that downloads this dataset and all other datasets directly from HuggingFace.
+The BaselineDataset also allows for more control over the splits and how many episodes you want to use (in cases where the `100` episodes aren't necessary).
+
+## Citation
+
+```
+```