Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
2-2022
Abstract
The quantal response (QR) model is widely used in Stackelberg security games (SSG) to model a bounded rational adversary. The QR model is a model of human response from among a large variety of prominent models known as discrete choice models. QR is the simplest type of discrete choice models and does not capture commonly observed phenomenon such as correlation among choices. We introduce the nested QR adversary model (based on nested logit model in discrete choice theory) in SSG which addresses shortcoming of the QR model. We present tractable approximation of the resulting equilibrium problem with nested QR adversary. We do so by deriving an interesting property of the equilibrium problem, namely a loosely coupled split into nested problems that mirrors the nested decision making by the adversary in the nested QR model. We show that each separate nested problem can be approximated efficiently and that the loosely coupled overall problem can be solved approximately by formulating it as a discretized version of a continuous dynamic program. Finally, we conduct experiments that show the scalability and parallelizability of our approach, as well as advantages of the nested QR model.
Discipline
Artificial Intelligence and Robotics
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of 36th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2022 Februrary 22 - March 1
First Page
1
Last Page
9
City or Country
Virtual Conference
Citation
MAI, Tien and SINHA, Arunesh.
Choices are not independent: Stackelberg security games with nested quantal response models. (2022). Proceedings of 36th AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2022 Februrary 22 - March 1. 1-9.
Available at: https://ink.library.smu.edu.sg/sis_research/6793
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.