Source code of our LIAM implementation in the double speaker-listener environment. The code is written in python 3, using Pytorch for the implementation of the deep networks. Other important packages are OpenAI Baselines, OpenAI gym, and the Multi-agent Particle Environment.
virtualenv -p python3 LIAM_ENV
cd LIAM_ENV
source bin/activate
pip install torch
pip install tensorflow
git clone https://github.com/openai/baselines.git
cd baselines
pip install -e .
cd ..
git clone https://github.com/shariqiqbal2810/multiagent-particle-envs.git
cd multiagent-particle-envs
pip install -e .
cd ..
pip install gym==0.9.4
pip install seaborn
git clone [email protected]:uoe-agents/LIAM.git
cd LIAM
cp multi_agent_env/simple_reference.py ../multiagent-particle-envs/multiagent/scenarios/.
python run_tests.py 0
If you use this repository in your work, please consider citing the LIAM paper
@article{papoudakis2021local,
title={Local Information Agent Modelling in Partially-Observable Environments},
author={Papoudakis, Georgios and Christianos, Filippos and Albrecht, Stefano V.},
journal={arXiv preprint arXiv:2006.09447},
year={2021}
}