Authors: Clément Scheirlinck, Rémy Chaput
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.
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.
After installing, open a Python shell (3.7+), and execute the following instructions:
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 allows creating new components (agents' profiles, reward functions, ...) to further customize the environment.
This project follows the Semver (Semantic Versioning): all versions respect
the <major>.<minor>.<patch> 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.
This GitHub repository includes actions that automatically test the package and build the documentation on each commit, and 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-<version>.tar.gz, and the built distribution
(wheel) at dist/ethical_smart_grid_simulator-<version>-py3-none-any.whl.
To publish these files to PyPi, use hatch publish.
The community guidelines are available in the CONTRIBUTING.md file; you can find a (short) summary below.
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.
Please do not use the issue tracker for support, to avoid cluttering it.
If you found a bug (an error raised, or something not working as expected), you can report it on the Issue Tracker.
Please try to be as precise as possible.
We very much welcome and appreciate contributions!
For fixing bugs, or improving the documentation, you can create a Pull Request.
New features are also welcome, but larger features should be discussed first in a new Discussion under the Ideas category.
All ideas, suggestions, and requests are also welcome for discussion.
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.
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
@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}
}