Code for the paper "Multi-Agent Sparse Interaction Modeling is an Anomaly Detection Problem" submitted to ICASSP 2024.
This repository develops SIA algorithm on StarCraft Multi-Agent Challenge benchmark. In addition, we compare it with multiple baselines including MAVEN, QTRAN and QPLEX.
To install requirements:
pip install -r requirements.txt
To train the approach in the paper, run this command:
python main.py
You can select the training algorithm by setting --config='sia' or other available choices
To modify the hyper-parameters of algorithms and environments, refer to:
src/config/algs/sia.yaml
src/config/default.yaml
src/config/envs/sc2.yaml
This repository is developed based on PyMARL. And we have cited the SMAC paper in our work.