https://github.com/ethicsai/ethical-smart-grid
Reinforcement learning environment for learning ethical behaviours in a SmartGrid use-case.
https://github.com/ethicsai/ethical-smart-grid
ai-ethics artificial-intelligence gym-environment machine-ethics python reinforcement-learning smart-grid
Last synced: 24 days ago
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Reinforcement learning environment for learning ethical behaviours in a SmartGrid use-case.
- Host: GitHub
- URL: https://github.com/ethicsai/ethical-smart-grid
- Owner: ethicsai
- License: other
- Created: 2022-09-13T13:19:27.000Z (about 3 years ago)
- Default Branch: master
- Last Pushed: 2024-07-19T11:34:35.000Z (about 1 year ago)
- Last Synced: 2025-08-27T23:53:53.574Z (about 1 month ago)
- Topics: ai-ethics, artificial-intelligence, gym-environment, machine-ethics, python, reinforcement-learning, smart-grid
- Language: Python
- Homepage: https://ethicsai.github.io/ethical-smart-grid/
- Size: 1.13 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.md
- Citation: CITATION.cff
- Codemeta: codemeta.json
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README
# Ethical Smart Grid Simulator
> Authors: Clément Scheirlinck, Rémy Chaput
[](https://github.com/ethicsai/ethical-smart-grid/actions/workflows/docs.yml)
[](https://github.com/ethicsai/ethical-smart-grid/actions/workflows/testing.yml)
[](https://doi.org/10.21105/joss.05410)
## Description
This is a third-party [Gym] environment, focusing on learning ethically-aligned
behaviours in a Smart Grid use-case.
A Smart Grid contains several *prosumer* (prosumer-consumer) agents that
interact in a shared environment by consuming and exchanging energy.
These agents have an energy need, at each time step, that they must satisfy
by consuming energy. However, they should respect a set of moral values as
they do so, i.e., exhibiting an ethically-aligned behaviour.
Moral values are encoded in the reward functions, which determine the
"correctness" of an agent's action, with respect to these moral values.
Agents receive rewards as feedback that guide them towards a better behaviour.
## Installation
You may install **Ethical Smart Grid** through:
- [PyPi], using `pip install ethical-smart-grid` (latest stable version);
- pip and GitHub, using `pip install git+https://github.com/ethicsai/ethical-smart-grid.git`
(you may specify the version at the end of the URL);
- GitHub, using `git clone https://github.com/ethicsai/ethical-smart-grid`
(development version, not stable).
If you also wish to use argumentation-based reward functions, please install
[AJAR] through `pip install git+https://github.com/ethicsai/ajar.git@v1.0.0`,
or `pip install -r requirements.txt` if you cloned this repository.
## Quick usage
After installing, open a Python shell (3.7+), and execute the following
instructions:
```python
from smartgrid import make_basic_smartgrid
from algorithms.qsom import QSOM
env = make_basic_smartgrid(max_step=10)
model = QSOM(env)
done = False
obs = env.reset()
while not done:
actions = model.forward(obs)
obs, rewards, terminated, truncated, _ = env.step(actions)
print(rewards)
model.backward(obs, rewards)
done = all(terminated) or all(truncated)
env.close()
```
This will initialize a SmartGrid environment, learning agents that use the QSOM
algorithm, and run the simulation for 10 steps (configurable through the `max_step=10`
argument).
To go further, please refer to the [documentation]; the [Custom scenario] and
[Adding a new model] pages can be particularly interesting to learn,
respectively, how to configure the environment, and how to implement a new
learning algorithm.
Finally, [extending the environment][Extending] allows creating new components
(agents' profiles, reward functions, ...) to further customize the environment.
## Versioning
This project follows the [Semver] (Semantic Versioning): all versions respect
the `..` format. The `patch` number is increased when a
bugfix is released. The `minor` number is increased when new features are added
that *do not* break the code public API, i.e., it is compatible with the
previous minor version. Finally, the `major` number is increased when a breaking
change is introduced; an important distinction is that such a change may not
be "important" in terms of lines of code, or number of features modified.
Simply changing a function's return type can be considered a breaking change
in the public API, and thus worthy of a "major" update.
## Building and testing locally
This GitHub repository includes actions that automatically [test][actions-test]
the package and [build][actions-docs] the documentation on each commit, and
[publish][actions-publish] the package to [PyPi] on each release.
Instructions to perform these steps locally are given here, for potential
new contributors or forks:
- *Running the tests*
Tests are defined using [unittest] and run through [pytest]; please install it
first: `pip install pytest`.
We must add the current folder to the `PYTHONPATH` environment variable to
let pytest import the `smartgrid` module when executing the tests:
`export PYTHONPATH=$PWD` (from the root of this repository). Then, launch all
tests with `pytest tests`.
- *Building the documentation*
The documentation is built with [Sphinx] and requires additional requirements;
to install them, use `pip install -r docs/requirements.txt`. Then, to build the
documentation, use `cd docs && make html`. The built documentation will be in
the `docs/build/html` folder. It can be cleaned using `make clean` while in the
`docs` folder. Additionally, the `source/modules` folder is automatically
generated from the Python docstrings in the source code; it can be safely
deleted (e.g., with `rm -r source/modules`) to force re-building all
documentation files.
- *Building and publishing releases*
This project uses [hatch] to manage the building and publishing process; please
install it with `pip install hatch` first.
To build the package, use `hatch build` at the root of this repository. This
will create the *source distribution* (sdist) at
`dist/ethica_smart_grid_simulator-.tar.gz`, and the *built distribution*
(wheel) at `dist/ethical_smart_grid_simulator--py3-none-any.whl`.
To publish these files to [PyPi], use `hatch publish`.
## Community
The community guidelines are available in the [CONTRIBUTING.md](CONTRIBUTING.md)
file; you can find a (short) summary below.
### Getting support
If you have a question (something that is not clear, how to get a specific
result, ...), do not hesitate to create a new [Discussion under the Q&A category](https://github.com/ethicsai/ethical-smart-grid/discussions/new?category=q-a).
Please do *not* use the issue tracker for support, to avoid cluttering it.
### Report a bug
If you found a bug (an error raised, or something not working as expected), you
can report it on the [Issue Tracker](https://github.com/ethicsai/ethical-smart-grid/issues/new).
Please try to be as *precise* as possible.
### Contributing
We very much welcome and appreciate contributions!
For fixing bugs, or improving the documentation, you can create a
[Pull Request](https://github.com/ethicsai/ethical-smart-grid/pulls).
New features are also welcome, but larger features should be discussed first in
a new [Discussion under the Ideas category](https://github.com/ethicsai/ethical-smart-grid/discussions/new?category=ideas).
All ideas, suggestions, and requests are also welcome for discussion.
## License
The source code is licensed under the [MIT License].
Some included data may be protected by other licenses, please refer to the
[LICENSE.md] file for details.
## Citation
If you use this package in your research, please cite the corresponding paper:
> Scheirlinck, C., Chaput, R., & Hassas, S. (2023). Ethical Smart Grid: a Gym
> environment for learning ethical behaviours. Journal of Open Source Software,
> 8(88), 5410. https://doi.org/10.21105/joss.05410
```bibtex
@article{Scheirlinck_Ethical_Smart_Grid_2023,
author = {Scheirlinck, Clément and Chaput, Rémy and Hassas, Salima},
doi = {10.21105/joss.05410},
journal = {Journal of Open Source Software},
month = aug,
number = {88},
pages = {5410},
title = {{Ethical Smart Grid: a Gym environment for learning ethical behaviours}},
url = {https://joss.theoj.org/papers/10.21105/joss.05410},
volume = {8},
year = {2023}
}
```
[Gym]: https://gymnasium.farama.org/
[AJAR]: https://github.com/ethicsai/ajar/
[documentation]: https://ethicsai.github.io/ethical-smart-grid/
[Custom scenario]: https://ethicsai.github.io/ethical-smart-grid/custom_scenario.html
[Adding a new model]: https://ethicsai.github.io/ethical-smart-grid/adding_model.html
[Extending]: https://ethicsai.github.io/ethical-smart-grid/extending/index.html
[Semver]: https://semver.org/
[PyPi]: https://pypi.org/project/ethical-smart-grid/
[unittest]: https://docs.python.org/3/library/unittest.html
[pytest]: https://pytest.org/
[actions-test]: https://github.com/ethicsai/ethical-smart-grid/actions/workflows/testing.yml
[actions-docs]: https://github.com/ethicsai/ethical-smart-grid/actions/workflows/docs.yml
[actions-publish]: https://github.com/ethicsai/ethical-smart-grid/actions/workflows/package.yml
[Sphinx]: https://www.sphinx-doc.org/
[hatch]: https://hatch.pypa.io/latest/
[MIT License]: https://choosealicense.com/licenses/mit/
[LICENSE.md]: LICENSE.md