Docs: add caveats and logo

README.md

@@ -1,10 +1,15 @@
+<div align="center">
+<img src="docs/img/qdax_logo.png" alt="qdax_logo" width="140"></img>
+</div>
+
+# QDax: Accelerated Quality-Diversity
+
 [![Documentation Status](https://readthedocs.org/projects/qdax/badge/?version=latest)](https://qdax.readthedocs.io/en/latest/?badge=latest)
 ![pytest](https://github.com/adaptive-intelligent-robotics/QDax/actions/workflows/ci.yaml/badge.svg?branch=main)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/adaptive-intelligent-robotics/QDax/blob/main/LICENSE)
 [![codecov](https://codecov.io/gh/adaptive-intelligent-robotics/QDax/branch/feat/add-codecov/graph/badge.svg)](https://codecov.io/gh/adaptive-intelligent-robotics/QDax)
 
 
-# QDax: Accelerated Quality-Diversity
 QDax is a tool to accelerate Quality-Diversity (QD) and neuro-evolution algorithms through hardware accelerators and massive parallelization. QD algorithms usually take days/weeks to run on large CPU clusters. With QDax, QD algorithms can now be run in minutes! ⏩ ⏩ 🕛
 
 QDax has been developed as a research framework: it is flexible and easy to extend and build on and can be used for any problem setting. Get started with simple example and run a QD algorithm in minutes here! [![Open All Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/adaptive-intelligent-robotics/QDax/blob/main/notebooks/mapelites_example.ipynb)
@@ -165,8 +170,11 @@ If you use QDax in your research and want to cite it in your work, please use:
 
 QDax was developed and is maintained by the [Adaptive & Intelligent Robotics Lab (AIRL)](https://www.imperial.ac.uk/adaptive-intelligent-robotics/) and [InstaDeep](https://www.instadeep.com/).
 
-<img align="center" src="docs/images/AIRL_logo.png" alt="AIRL_Logo" width="220"/> <img align="center" src="docs/images/instadeep_logo.png" alt="InstaDeep_Logo" width="220"/>
+<div align="center">
+<img align="center" src="docs/img/AIRL_logo.png" alt="AIRL_Logo" width="220"/> <img align="center" src="docs/img/instadeep_logo.png" alt="InstaDeep_Logo" width="220"/>
+</div>
 
+<div align="center">
 <a href="https://github.com/limbryan" title="Bryan Lim"><img src="https://github.com/limbryan.png" height="auto" width="50" style="border-radius:50%"></a>
 <a href="https://github.com/maxiallard" title="Maxime Allard"><img src="https://github.com/maxiallard.png" height="auto" width="50" style="border-radius:50%"></a>
 <a href="https://github.com/Lookatator" title="Luca Grilloti"><img src="https://github.com/Lookatator.png" height="auto" width="50" style="border-radius:50%"></a>
@@ -179,3 +187,4 @@ QDax was developed and is maintained by the [Adaptive & Intelligent Robotics Lab
 <a href="https://github.com/GRichard513" title="Guillaume Richard"><img src="https://github.com/GRichard513.png" height="auto" width="50" style="border-radius:50%"></a>
 <a href="https://github.com/flajolet" title="Arthur Flajolet"><img src="https://github.com/flajolet.png" height="auto" width="50" style="border-radius:50%"></a>
 <a href="https://github.com/remidebette" title="Rémi Debette"><img src="https://github.com/remidebette.png" height="auto" width="50" style="border-radius:50%"></a>
+</div>

docs/caveats.md

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+# QDax Caveats
+
+Here is a few caveats one should be aware of when using QDax.
+
+## Use of auto reset for Brax environments
+The use of `auto_reset` can be tricky and lead to problems and/or unwanted behaviors. By defaults in our examples, we set auto reset equals True, so the samples collected in the Replay Buffer are good quality samples and stay within the distribution of interest. This is particularly important in the case of PGAME, where putting auto reset to False could lead to important decrease in data efficiency and final performance.
+
+## In-place replacement of state descriptors in QDTransition
+The state descriptor from Brax environments is stored in a dictionary. The retrievement of this data when building the QDTransition in a step is hence tricky. The state descriptor must be stored in a variable before applying a environment step, because an in-place replacement is going to occur during the step function of Brax.
+
+One should take inspiration from the `play_step` function from our examples.

docs/notebooks

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-../notebooks/
+../examples/notebooks/

mkdocs.yml

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       toggle:
         icon: material/weather-sunny
         name: Switch to light mode
-
   features:
     - navigation.tracking
     - navigation.tabs
@@ -109,6 +108,7 @@ nav:
   - Home: index.md
   - Installation: installation.md
   - Overview: overview.md
+  - Caveats: caveats.md
   - Guides:
     - Contributing: guides/CONTRIBUTING.md
   - Examples: