Mosaik Environment for palaestrAI.
Project description
Adversarial Resilience Learning --- Mosaik Environment
This projects contains the interface between palaestrAI and mosaik, the mosaik environment.
Introduction
This package allows to use worlds created with the co-simulation framework mosaik as environment in palaestrAI. The package was developed with MIDAS in mind but should work for arbitrary mosaik worlds. See documenation for more details on how to import a world.
Installation
palaestrAI-mosaik is written in Python. It provides a setup.py
that installs
the minimal set of packages to run ARL Mosaik. Use, preferable in a
virtual environment::
./setup.py install
or, for development::
pip install -e .
Additional requirements are listed in the requirements.txt::
pip install -r requirements.txt
Alternatively, you can install it directly with pip
pip install palaestrai-mosaik
Usage
To run an example you have to install the requirements.txt.
Under tests, you find the example_experiment_midas.yml
that should be
passed to the palaestrai command line interface::
palaestrai experiment-start /path/to/tests/example_experiment_midas.yml
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
File details
Details for the file palaestrai-mosaik-0.6.0.tar.gz
.
File metadata
- Download URL: palaestrai-mosaik-0.6.0.tar.gz
- Upload date:
- Size: 33.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.0 CPython/3.9.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | bc8ce0b1fe9be7e786723f47c77bfc431b3afc4ea1c9d89e62e2dbec7e48ddbb |
|
MD5 | 0095e5b1d957cbbd688bc5efbf3d3bff |
|
BLAKE2b-256 | 6e5206b953d8300ce88da128ce6bfd3a09d02b97bf64c5a442d4b7e22ecb7846 |
File details
Details for the file palaestrai_mosaik-0.6.0-py3-none-any.whl
.
File metadata
- Download URL: palaestrai_mosaik-0.6.0-py3-none-any.whl
- Upload date:
- Size: 25.9 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.0 CPython/3.9.16
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | cf929782aed2ca472f2f662de44c072a1fbfdf7d041af291cee239bd6710734c |
|
MD5 | 24df0128bfeedbd5ffee8c82f1fa05ae |
|
BLAKE2b-256 | 041be062d2605723af2c3cf7e67d4d81ec685f032936b9e4ad4e31eea16471fa |