Gym-Robotics
Details and documentation on these robotics environments are available in OpenAI's blog post and the accompanying technical report.
Requirements:
- Python 3.7 to 3.10
- Gym v0.26
- NumPy 1.18+
- Mujoco 2.2.2
If you use these environments, please cite the following paper:
@misc{1802.09464,
Author = {Matthias Plappert and Marcin Andrychowicz and Alex Ray and Bob McGrew and Bowen Baker and Glenn Powell and Jonas Schneider and Josh Tobin and Maciek Chociej and Peter Welinder and Vikash Kumar and Wojciech Zaremba},
Title = {Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research},
Year = {2018},
Eprint = {arXiv:1802.09464},
}
New MuJoCo Python Bindings
The latest version and future versions of the MuJoCo environments will no longer depend on mujoco-py. Instead the new mujoco python bindings will be the required dependency for future gym MuJoCo environment versions. Old gym MuJoCo environment versions that depend on mujoco-py will still be kept but unmaintained.
Dependencies for old MuJoCo environments can still be installed by pip install gym_robotics[mujoco_py].
Metadata
Release files for gym-robotics 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| gym-robotics-1.0.1.tar.gz | 1.5 MB | Without provenance | Details for gym-robotics-1.0.1.tar.gz |
Release files / gym-robotics-1.0.1.tar.gz
| Download URL | gym-robotics-1.0.1.tar.gz |
|---|---|
| Size | 1.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6ad3e4d0f4a8e1cb66b60a311c7e5d398eeaa40ff0be6d39e9d33fb3a4c66a67
|
|
BLAKE2b-256 checksum How to use checksums |
b466ff3be32eb370c9fe2f0857f2523e4bc2144d8e7dd22f50c8fc9a0bcd44a0
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.9.14
|
Security for gym-robotics 1.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.