| Name | flatland-rl JSON |
| Version |
4.0.3
JSON |
| download |
| home_page | None |
| Summary | Multi Agent Reinforcement Learning on Trains |
| upload_time | 2024-04-23 14:10:30 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2019 SBB AG Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
flatland
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
aiosignal
appdirs
asttokens
async-timeout
attr
attrs
backcall
boto3
botocore
certifi
charset-normalizer
click
cloudpickle
comm
contourpy
crowdai-api
cycler
dataclasses
decorator
docker-pycreds
executing
farama-notifications
filelock
fonttools
frozenlist
gitdb
gitpython
graphviz
gymnasium
idna
importlib-resources
ipycanvas
ipyevents
ipython
ipywidgets
jedi
jmespath
jsonschema
jsonschema-specifications
jupyterlab-widgets
kiwisolver
lxml
matplotlib
matplotlib-inline
msgpack
msgpack-numpy
networkx
numpy
packaging
pandas
parso
pathtools
pettingzoo
pexpect
pickleshare
pillow
prompt-toolkit
protobuf
psutil
ptyprocess
pure-eval
pyglet
pygments
pyparsing
python-dateutil
python-gitlab
pytz
pyyaml
ray
recordtype
redis
referencing
requests
requests-toolbelt
rpds-py
s3transfer
seaborn
sentry-sdk
setproctitle
six
smmap
stack-data
supersuit
svgutils
timeout-decorator
tinyscaler
traitlets
typing-extensions
tzdata
urllib3
wandb
wcwidth
widgetsnbextension
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
🚂 Flatland
========
[](https://github.com/flatland-association/flatland-rl/actions/workflows/main.yml)
Flatland is a open-source toolkit for developing and comparing Multi-Agent Reinforcement Learning algorithms in little
(or ridiculously large!) gridworlds.
[The official website](https://www.flatland-association.org/) contains full details about the environment and problem
statement.
Flatland is tested with Python 3.8, 3.9 and 3.10 on modern versions of macOS, Linux and Windows. You may encounter
problems with graphical rendering if you use WSL.
🏆 Challenges
---
This library was developed specifically for the
AIcrowd [Flatland challenges](http://flatland.aicrowd.com/research/top-challenge-solutions.html) in which we strongly
encourage you to take part in!
- [Flatland 3 Challenge](https://www.aicrowd.com/challenges/flatland-3)
- [AMLD 2021 Challenge](https://www.aicrowd.com/challenges/flatland)
- [NeurIPS 2020 Challenge](https://www.aicrowd.com/challenges/neurips-2020-flatland-challenge/)
- [2019 Challenge](https://www.aicrowd.com/challenges/flatland-challenge)
📦 Setup
---
### Setup virtual environment
Set up a virtual environment using your preferred method (we suggest the built-in `venv`) and activate it.
You can use your IDE to do this or by using the command line:
```shell
python -m venv .venv
source .venv/bin/activate
```
### Stable release
Install Flatland using pip:
```shell
python -m pip install flatland-rl
```
This is the preferred method to install Flatland, as it will always install the most recent stable release.
👥 Credits
---
This library was developed
by [SBB](https://www.sbb.ch/en/), [Deutsche Bahn](https://www.deutschebahn.com/), [SNCF](https://www.sncf.com/en),
[AIcrowd](https://www.aicrowd.com/) and [numerous contributors](http://flatland.aicrowd.com/misc/credits.html) from the
flatland community.
➕ Contributions
---
Please follow the [Contribution Guidelines](./CONTRIBUTING.md) for more details on how you can successfully contribute
to the project. We enthusiastically look forward to your contributions!
💬 Communication
---
* [Issue Tracker](https://github.com/flatland-association/flatland-rl/issues/)
🔗 Partners
---
<a href="https://sbb.ch" target="_blank" style="margin-right:30px"><img src="https://annpr2020.ch/wp-content/uploads/2020/06/SBB.png" alt="SBB" width="140"/></a>
<a href="https://www.deutschebahn.com/" target="_blank" style="margin-right:30px"><img src="https://i.imgur.com/pjTki15.png" alt="DB" width="140"/></a>
<a href="https://www.sncf.com/en" target="_blank" style="margin-right:30px"><img src="https://iconape.com/wp-content/png_logo_vector/logo-sncf.png" alt="SNCF" width="140"/></a>
<a href="https://www.aicrowd.com" target="_blank"><img src="https://i.imgur.com/kBZQGI9.png" alt="AIcrowd" width="140"/></a>
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"description": "\ud83d\ude82 Flatland\n========\n\n\n\n[](https://github.com/flatland-association/flatland-rl/actions/workflows/main.yml)\n\nFlatland is a open-source toolkit for developing and comparing Multi-Agent Reinforcement Learning algorithms in little\n(or ridiculously large!) gridworlds.\n\n[The official website](https://www.flatland-association.org/) contains full details about the environment and problem\nstatement.\n\nFlatland is tested with Python 3.8, 3.9 and 3.10 on modern versions of macOS, Linux and Windows. You may encounter\nproblems with graphical rendering if you use WSL.\n\n\ud83c\udfc6 Challenges\n---\n\nThis library was developed specifically for the\nAIcrowd [Flatland challenges](http://flatland.aicrowd.com/research/top-challenge-solutions.html) in which we strongly\nencourage you to take part in!\n\n- [Flatland 3 Challenge](https://www.aicrowd.com/challenges/flatland-3)\n- [AMLD 2021 Challenge](https://www.aicrowd.com/challenges/flatland)\n- [NeurIPS 2020 Challenge](https://www.aicrowd.com/challenges/neurips-2020-flatland-challenge/)\n- [2019 Challenge](https://www.aicrowd.com/challenges/flatland-challenge)\n\n\ud83d\udce6 Setup\n---\n\n### Setup virtual environment\n\nSet up a virtual environment using your preferred method (we suggest the built-in `venv`) and activate it.\nYou can use your IDE to do this or by using the command line:\n\n```shell\npython -m venv .venv\nsource .venv/bin/activate\n```\n\n### Stable release\n\nInstall Flatland using pip:\n\n```shell\npython -m pip install flatland-rl\n```\n\nThis is the preferred method to install Flatland, as it will always install the most recent stable release.\n\n\ud83d\udc65 Credits\n---\n\nThis library was developed\nby [SBB](https://www.sbb.ch/en/), [Deutsche Bahn](https://www.deutschebahn.com/), [SNCF](https://www.sncf.com/en),\n[AIcrowd](https://www.aicrowd.com/) and [numerous contributors](http://flatland.aicrowd.com/misc/credits.html) from the\nflatland community.\n\n\u2795 Contributions\n---\nPlease follow the [Contribution Guidelines](./CONTRIBUTING.md) for more details on how you can successfully contribute\nto the project. We enthusiastically look forward to your contributions!\n\n\ud83d\udcac Communication\n---\n\n* [Issue Tracker](https://github.com/flatland-association/flatland-rl/issues/)\n\n\ud83d\udd17 Partners\n---\n\n<a href=\"https://sbb.ch\" target=\"_blank\" style=\"margin-right:30px\"><img src=\"https://annpr2020.ch/wp-content/uploads/2020/06/SBB.png\" alt=\"SBB\" width=\"140\"/></a>\n<a href=\"https://www.deutschebahn.com/\" target=\"_blank\" style=\"margin-right:30px\"><img src=\"https://i.imgur.com/pjTki15.png\" alt=\"DB\" width=\"140\"/></a>\n<a href=\"https://www.sncf.com/en\" target=\"_blank\" style=\"margin-right:30px\"><img src=\"https://iconape.com/wp-content/png_logo_vector/logo-sncf.png\" alt=\"SNCF\" width=\"140\"/></a>\n<a href=\"https://www.aicrowd.com\" target=\"_blank\"><img src=\"https://i.imgur.com/kBZQGI9.png\" alt=\"AIcrowd\" width=\"140\"/></a>\n",
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