This is implementation of team-coordination between multiple agents in presence of adversaries using graphs as mentioned in our paper:
Manshi Limbu, Sara Oughourli, Zechen Hu, Xuan Wang, Xuesu Xiao, Daigo Shishika, Team Coordination on Graphs with State-Dependent Edge Costs
- networkx(>=3.0)
- numpy(>=1.24.2)
- matplotlib(>=3.7.0)
pip3 install -r requirements.txt
cd team-coordination
python3 quickCompare.py
For --nodes
param, add number of nodes and for riskyedge
param, add risk edge ratio (more info in the paper).
cd team-coordination
python3 graphCompare.py --nodes 10 --riskedge 0.2
You can choose between following algorithms:
-
jsg
: Converts multi-agent problem as single agent path planning algorithm. -
cjsg
: Heirarchial path planning algorithm that alleviates the curse of dimesionality casued byjsg
.
Please cite our paper if you use this code in your own work:
@INPROCEEDINGS{10341820,
author={Limbu, Manshi and Hu, Zechen and Oughourli, Sara and Wang, Xuan and Xiao, Xuesu and Shishika, Daigo},
booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
title={Team Coordination on Graphs with State-Dependent Edge Costs},
year={2023},
volume={},
number={},
pages={679-684},
keywords={Costs;Statistical analysis;Scalability;Path planning;Planning;Complexity theory;Game theory},
doi={10.1109/IROS55552.2023.10341820}}