MetaGym: environments for benchmarking Reinforcement Learning and Meta Reinforcement Learning
Project description
MetaGym
MetaGym provides abundant environments for benchmarking Reinforcement Learning and Meta Reinforcement Learning
Environments Updating
-
LiftSim:Simulator for Evelvator Dispatching (Sep, 2019)
-
Quadrotor: 3D Quadrotor simulator for different tasks (Mar, 2020)
-
Quadrupedal: Quadrupedal robot adapting to different terrains (Seq, 2021)
-
MetaMaze: Meta maze environment for 3D visual navigation (Oct, 2021)
-
Navigator2D: Simple 2D navigator meta environment (Oct, 2021)
-
MetaLocomotion: Locomotion simulator with diverse geometries (June, 2022)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file metagym-0.1.1.tar.gz
.
File metadata
- Download URL: metagym-0.1.1.tar.gz
- Upload date:
- Size: 132.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.6.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5223899d04b9a9678b16daedc03e56af60d8e007836e417a9206e169aaee2f64 |
|
MD5 | 4abb86ab778772cee8519b71ff8c4a05 |
|
BLAKE2b-256 | 3d15305856c4818a3f5b10f8cbcd8fcf0d4d79b5146ea83aaea61a215c0544ad |
File details
Details for the file metagym-0.1.1-py2.py3-none-any.whl
.
File metadata
- Download URL: metagym-0.1.1-py2.py3-none-any.whl
- Upload date:
- Size: 17.9 MB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.6.0 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.8.9
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3108181cb8ab03ed9fb12a822365c4c5d770af0c942aee5631efb26205e34b22 |
|
MD5 | 6b6ec3c90f611412babea61131e0f952 |
|
BLAKE2b-256 | 3cf9d158b069c401dff5d0257222d6ee4dcc1085b0a56fc73825b098e8ef07a2 |