Algorithmic Environments from OpenAI Gym
Project description
gym-algorithmic
Environments
Copy-v0
DuplicatedInput-v0
RepeatCopy-v0
Reverse-v0
ReversedAddition-v0
ReversedAddition3-v0
Documentation credit: https://github.com/openai/gym/pull/2334
Usage
$ pip install gym-algorithmic
import gym
import gym_algorithmic
gym.make("Copy-v0")
Citation
This repository contains the algorithmic environments previously present in OpenAI Gym prior to Gym version 0.19.0. These environments were introduced in the paper Learning Simple Algorithms from Examples
@inproceedings{Zaremba2016LearningSA,
title={Learning Simple Algorithms from Examples},
author={Wojciech Zaremba and Tomas Mikolov and Armand Joulin and R. Fergus},
booktitle={ICML},
year={2016}
}
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
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file gym-algorithmic-0.0.1.tar.gz.
File metadata
- Download URL: gym-algorithmic-0.0.1.tar.gz
- Upload date:
- Size: 7.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/3.10.0 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
1bea52ab69b5b58a5a86af089305dab030e6b31d1bd6631987348b57209000a7
|
|
| MD5 |
df75d09f9c5f928c4c0ca140b048361b
|
|
| BLAKE2b-256 |
67c7c5a6523356bedc7f17422e7ffa93c6e5aad5aec50de7b09298432f37f86c
|
File details
Details for the file gym_algorithmic-0.0.1-py3-none-any.whl.
File metadata
- Download URL: gym_algorithmic-0.0.1-py3-none-any.whl
- Upload date:
- Size: 8.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/3.10.0 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.10
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d6ca0ed898867f0d91b633a629e9264ab3fdba0a00246afac34cd641875f570b
|
|
| MD5 |
8501aa35dd2c66d6d9ce59da2a35c893
|
|
| BLAKE2b-256 |
77106fd6e7dd5b66bc45c9bb7cfa01e4f0e05c4d308bd14ac953179cd42e9cc1
|