Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems
Wenqing Zheng, Qiangqiang Guo, Hao Frank Yang, Peihao Wang, Zhangyang Wang
Abstract
Multi-agent control is a central theme in the Cyber-Physical Systems (CPS). However, current control methods either receive non-Markovian states due to insufficient sensing and decentralized design, or suffer from poor convergence. This paper presents the Delayed Propagation Transformer (DePT), a new transformer-based model that specializes in the global modeling of CPS while taking into account the immutable constraints from the physical world. DePT induces a cone-shaped spatial-temporal attention prior, which injects the information propagation and aggregation principles and enables a global view. With physical constraint inductive bias baked into its design, our DePT is ready to plug and play for a broad class of multi-agent systems. The experimental results on one of the most challenging CPS -- network-scale traffic signal control system in the open world -- show that our model outperformed the state-of-the-art expert methods on synthetic and real-world datasets. Our codes are released at: https://github.com/VITA-Group/DePT.
BibTeX
@inproceedings{
zheng2021delayed,
title={Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems},
author={Wenqing Zheng and Qiangqiang Guo and Hao Frank Yang and Peihao Wang and Zhangyang Wang},
booktitle={Advances in Neural Information Processing Systems},
editor={A. Beygelzimer and Y. Dauphin and P. Liang and J. Wortman Vaughan},
year={2021},
url={https://openreview.net/forum?id=DJ6fmWG4qvW}
}