New index.rst, added assests

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Dominik Moritz Roth 2023-12-05 18:16:47 +01:00
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commit 57c3d36490
6 changed files with 1107 additions and 14 deletions

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.. fancy_gym documentation master file, created by
sphinx-quickstart on Sat Sep 30 17:30:55 2023.
You can adapt this file completely to your liking, but it should at least
contain the root `toctree` directive.
Fancy Gym
=========
Welcome to Fancy Gym's documentation!
=====================================
Built upon the foundation of
`Gymnasium <https://gymnasium.farama.org/>`__ (a maintained fork of
OpenAIs renowned Gym library) ``fancy_gym`` offers a comprehensive
collection of reinforcement learning environments.
Key Features
------------
- **New Challenging Environments**: ``fancy_gym`` includes several new
environments (Panda Box Pushing, Table Tennis, etc.) that present a
higher degree of difficulty, pushing the boundaries of reinforcement
learning research.
- **Support for Movement Primitives**: ``fancy_gym`` supports a range
of movement primitives (MPs), including Dynamic Movement Primitives
(DMPs), Probabilistic Movement Primitives (ProMP), and Probabilistic
Dynamic Movement Primitives (ProDMP).
- **Upgrade to Movement Primitives**: With our framework, its
straightforward to transform standard Gymnasium environments into
environments that support movement primitives.
- **Benchmark Suite Compatibility**: ``fancy_gym`` makes it easy to
access renowned benchmark suites such as `DeepMind
Control <https://deepmind.com/research/publications/2020/dm-control-Software-and-Tasks-for-Continuous-Control>`__
and `Metaworld <https://meta-world.github.io/>`__, whether you want
to use them in the regular step-based setting or using MPs.
- **Contribute Your Own Environments**: If youre inspired to create
custom gym environments, both step-based and with movement
primitives, this
`guide <https://gymnasium.farama.org/tutorials/gymnasium_basics/environment_creation/>`__
will assist you. We encourage and highly appreciate submissions via
PRs to integrate these environments into ``fancy_gym``.
.. toctree::
:maxdepth: 5
:caption: Contents:
:maxdepth: 3
:caption: User Guide
guide/installation
guide/episodic_rl
guide/basic_usage
guide/upgrading_envs
.. toctree::
:maxdepth: 3
:caption: Examples
examples/general
examples/dmc
examples/metaworld
examples/open_ai
examples/movement_primitives
examples/mp_params_tuning
examples/replanning_envs
.. toctree::
:maxdepth: 3
:caption: Environments
envs/fancy/index
envs/airhockey
envs/dmc
envs/meta
envs/open_ai
.. toctree::
:maxdepth: 3
:caption: API
api
envs/index
Indices and tables
==================
Citing the Project
------------------
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`
To cite this repository in publications:
.. code:: bibtex
@software{fancy_gym,
title = {Fancy Gym},
author = {Otto, Fabian and Celik, Onur and Roth, Dominik and Zhou, Hongyi},
abstract = {Fancy Gym: Unifying interface for various RL benchmarks with support for Black Box approaches.},
url = {https://github.com/ALRhub/fancy_gym},
organization = {Autonomous Learning Robots Lab (ALR) at KIT},
}
Icon Attribution
----------------
The icon is based on the
`Gymnasium <https://github.com/Farama-Foundation/Gymnasium>`__ icon as
can be found
`here <https://gymnasium.farama.org/_static/img/gymnasium_black.svg>`__.
=================
.. raw:: html
<div style="text-align: center;">
<a href="https://alr.anthropomatik.kit.edu/"><img src="_static/imgs/alr.svg" style="margin: 5%; width: 20%;"></a>
<a href="https://www.kit.edu/"><img src="_static/imgs/kit.svg" style="margin: 5%; width: 20%;"></a>
<a href="https://uni-tuebingen.de/"><img src="_static/imgs/uni_tuebingen.svg" style="margin: 5%; width: 20%;"></a>
</div>