Entity Gym
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.
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Release files for entity-gym 0.1.10
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| entity_gym-0.1.10.tar.gz | 39.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| entity_gym-0.1.10-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 91.5 kB
Release files / entity_gym-0.1.10.tar.gz
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Release files / entity_gym-0.1.10-py3-none-any.whl
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