Skip to main content

Entity Gym

Project description

Entity Gym

Actions Status PyPI Documentation Status Discord

Entity Gym is an open source Python library that defines an entity based API for reinforcement learning environments. Entity Gym extends the standard paradigm of fixed-size observation spaces by allowing observations to contain dynamically-sized lists of entities. This enables a seamless and highly efficient interface with simulators, games, and other complex environments whose state can be naturally expressed as a collection of entities.

The enn-trainer library can be used to train agents for Entity Gym environments.

Installation

pip install entity-gym

Usage

You can find tutorials, guides, and an API reference on the Entity Gym documentation website.

Examples

A number of simple example environments can be found in entity_gym/examples. More complex examples can be found in the ENN-Zoo project, which contains Entity Gym bindings for Procgen, Griddly, MicroRTS, VizDoom, and CodeCraft.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

entity-gym-0.1.4.tar.gz (39.8 kB view details)

Uploaded Source

Built Distribution

entity_gym-0.1.4-py3-none-any.whl (50.7 kB view details)

Uploaded Python 3

File details

Details for the file entity-gym-0.1.4.tar.gz.

File metadata

  • Download URL: entity-gym-0.1.4.tar.gz
  • Upload date:
  • Size: 39.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.13.0-1031-azure

File hashes

Hashes for entity-gym-0.1.4.tar.gz
Algorithm Hash digest
SHA256 0946de3ffa3d1a99d4b93415f91905014154aaa48f3d967f55aede6f74d36e35
MD5 1488c526c6dfc780115ac8b51ed7b15a
BLAKE2b-256 f9470d458de06c2311a45650ee1c366415b146f9bde0f9401d664f6327b5680e

See more details on using hashes here.

File details

Details for the file entity_gym-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: entity_gym-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 50.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.13 CPython/3.8.12 Linux/5.13.0-1031-azure

File hashes

Hashes for entity_gym-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 f5401a87d6cb207ce3f9c6a7ca01c71e7c03af886244e42325fc8368a4a005d2
MD5 9d80b0e4da212887123b441f3ec88b4d
BLAKE2b-256 5f290bc678354b1d7598b1c2037a29bfd5bb0f92e2d1681775c7bceb419f1f74

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page