https://github.com/condensedai/gym-toricgame
Reinforcement learning environment for the Toric Game
Science Score: 10.0%
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Links to: arxiv.org -
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○Scientific vocabulary similarity
Low similarity (3.9%) to scientific vocabulary
Last synced: 10 months ago
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Repository
Reinforcement learning environment for the Toric Game
Basic Info
- Host: GitHub
- Owner: condensedAI
- License: mit
- Language: Python
- Default Branch: main
- Size: 3.91 KB
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 5 years ago
· Last pushed over 5 years ago
https://github.com/condensedAI/gym-toricgame/blob/main/
# The Toric Game
This repository implements a reinforcement learning environment for the toric code,
with perspectives (see [arxiv](arxiv.org)), on which quantum error correction can
be trained.
## Usage
The best way to use this environment, is to use [SciGym](https://github.com/hendrikpn/scigym) instead of this repo as a standalone.
Using [SciGym](https://github.com/hendrikpn/scigym), you can initialize this environment through
**Initializing the environment**
```python
import scigym
env = scigym.make("toricgame-v0")
```
## Environment description
TODO
## TRAINING
Launch the file train.py with corresponding arguments (see in the file)
## EVALUATION
Launch the file evaluate.py with corresponding arguments (see in the file)
Owner
- Name: condensedAI
- Login: condensedAI
- Kind: organization
- Repositories: 2
- Profile: https://github.com/condensedAI
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Dependencies
setup.py
pypi
- gym *