mirror of
https://github.com/saymrwulf/stable-baselines3.git
synced 2026-05-18 21:30:19 +00:00
944dfdafe4
* Fix big when saving/loading q-net alone * Rename variables to match SB3-contrib * Update docker image * Set min version for tensorboard * Add SB3-Contrib to doc * Update DQN * Apply suggestions from code review Co-authored-by: Adam Gleave <adam@gleave.me> * Update wording Co-authored-by: Adam Gleave <adam@gleave.me>
97 lines
2.7 KiB
ReStructuredText
97 lines
2.7 KiB
ReStructuredText
.. _sb3_contrib:
|
|
|
|
==================
|
|
SB3 Contrib
|
|
==================
|
|
|
|
We implement experimental features in a separate contrib repository:
|
|
`SB3-Contrib`_
|
|
|
|
This allows Stable-Baselines3 (SB3) to maintain a stable and compact core, while still
|
|
providing the latest features, like Truncated Quantile Critics (TQC) or
|
|
Quantile Regression DQN (QR-DQN).
|
|
|
|
Why create this repository?
|
|
~~~~~~~~~~~~~~~~~~~~~~~~~~~
|
|
|
|
Over the span of stable-baselines and stable-baselines3, the community
|
|
has been eager to contribute in form of better logging utilities,
|
|
environment wrappers, extended support (e.g. different action spaces)
|
|
and learning algorithms.
|
|
|
|
However sometimes these utilities were too niche to be considered for
|
|
stable-baselines or proved to be too difficult to integrate well into
|
|
the existing code without creating a mess. sb3-contrib aims to fix this by not
|
|
requiring the neatest code integration with existing code and not
|
|
setting limits on what is too niche: almost everything remotely useful
|
|
goes!
|
|
We hope this allows us to provide reliable implementations
|
|
following stable-baselines usual standards (consistent style, documentation, etc)
|
|
beyond the relatively small scope of utilities in the main repository.
|
|
|
|
Features
|
|
--------
|
|
|
|
See documentation for the full list of included features.
|
|
|
|
**RL Algorithms**:
|
|
|
|
- `Truncated Quantile Critics (TQC)`_
|
|
- `Quantile Regression DQN (QR-DQN)`_
|
|
|
|
**Gym Wrappers**:
|
|
|
|
- `Time Feature Wrapper`_
|
|
|
|
Documentation
|
|
-------------
|
|
|
|
Documentation is available online: https://sb3-contrib.readthedocs.io/
|
|
|
|
Installation
|
|
------------
|
|
|
|
To install Stable-Baselines3 contrib with pip, execute:
|
|
|
|
::
|
|
|
|
pip install sb3-contrib
|
|
|
|
We recommend to use the ``master`` version of Stable Baselines3 and SB3-Contrib.
|
|
|
|
To install Stable Baselines3 ``master`` version:
|
|
|
|
::
|
|
|
|
pip install git+https://github.com/DLR-RM/stable-baselines3
|
|
|
|
To install Stable Baselines3 contrib ``master`` version:
|
|
|
|
::
|
|
|
|
pip install git+https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
|
|
|
|
|
|
Example
|
|
-------
|
|
|
|
SB3-Contrib follows the SB3 API and folder structure. So, if you are familiar with SB3,
|
|
using SB3-Contrib should be easy too.
|
|
|
|
Here is an example of training a Quantile Regression DQN (QR-DQN) agent on the CartPole environment.
|
|
|
|
.. code-block:: python
|
|
|
|
from sb3_contrib import QRDQN
|
|
|
|
policy_kwargs = dict(n_quantiles=50)
|
|
model = QRDQN("MlpPolicy", "CartPole-v1", policy_kwargs=policy_kwargs, verbose=1)
|
|
model.learn(total_timesteps=10000, log_interval=4)
|
|
model.save("qrdqn_cartpole")
|
|
|
|
|
|
|
|
.. _SB3-Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib
|
|
.. _Truncated Quantile Critics (TQC): https://arxiv.org/abs/2005.04269
|
|
.. _Quantile Regression DQN (QR-DQN): https://arxiv.org/abs/1710.10044
|
|
.. _Time Feature Wrapper: https://arxiv.org/abs/1712.00378
|