Haimin Hu1, Gabriele Dragotto1, Zixu Zhang, Kaiqu Liang, Bartolomeo Stellato, Jaime F. Fisac
1equal contribution
Published as a conference paper at RSS'2024.
This repository implements Branch and Play (B&P), an efficient and exact game-theoretic algorithm that provably converges to a socially optimal order of play and its Stackelberg (leader-follower) equilibrium. As a subroutine for B&P, we also implement sequential trajectory planning (STP) as a game solver to scalably compute a valid local Stackelberg equilibrium for any given order of play. The repository is primarily developed and maintained by Haimin Hu and Gabriele Dragotto.
Click to watch our spotlight video:
We provide an air traffic control (ATC) example in the Notebook. This Notebook comprises three sections, each dedicated to a closed-loop simulation using a different method: Branch and Play, first-come-first-served baseline, and Nash ILQ Game baseline.
Distributed under the MIT License. See LICENSE for more information.
- Haimin Hu - @HaiminHu - haiminh@princeton.edu
- Gabriele Dragotto - @GabrieleDrag8 - hello@dragotto.net
If you found this repository helpful, please consider citing our paper.
@inproceedings{hu2024plays,
title={Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots},
author={Hu, Haimin and Dragotto, Gabriele and Zhang, Zixu and Liang, Kaiqu and Stellato, Bartolomeo and Fisac, Jaime F},
booktitle={Proceedings of Robotics: Science and Systems},
year={2024}
}