A Multi-agent reinforcement-learning simulator framework.
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Phantom is a multi-agent reinforcement-learning simulator built on top of RLlib.
The main requirements for installing Phantom are a modern Python installation (3.8 minimum) and access to the pip Python package manager.
A list of Python packages required by Phantom is given in the
requirements.txt
files in each respective directory. The required packages can be
installed by running:
make install-deps
Phantom can be installed as libraries with the command::
make install
To use the network plotting feature for Tensorboard the following additional packages are required:
- matplotlib
- networkx
With Phantom installed you can run the provided supply-chain
sample experiment
with the command:
phantom examples/environments/supply-chain/supply-chain.py
Change the script for any of the other provided experiments in the examples directory.
Thank you for your interest in contributing to Phantom!
We invite you to contribute enhancements. Upon review you will be required to complete the Contributor License Agreement (CLA) before we are able to merge.
If you have any questions about the contribution process, please feel free to send an email to open_source@jpmorgan.com.
Find the paper on Arxiv Phantom -- An RL-driven framework for agent-based modeling of complex economic systems and markets or use the following BibTeX:
@inproceedings{ardon2023phantom,
title={Phantom-A RL-driven Multi-Agent Framework to Model Complex Systems},
author={Ardon, Leo and Vann, Jared and Garg, Deepeka and Spooner, Thomas and Ganesh, Sumitra},
booktitle={Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems},
pages={2742--2744},
year={2023},
keywords = {Artificial Intelligence, Multiagent Systems, Reinforcement Learning}
}
Distributed under the Apache 2.0 License. See LICENSE
for more information.