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@inproceedings{2214539,
author = {Klaška, David and Kučera, Antonín and Musil, Vít and Řehák, Vojtěch},
address = {Neuveden},
booktitle = {21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022.},
doi = {http://dx.doi.org/10.5555/3535850.3536068},
editor = {Piotr Faliszewski, Viviana Mascardi, Catherine Pelachaud, Matthew E. Taylor},
keywords = {Security Games; Adversarial Patrolling},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Neuveden},
isbn = {978-1-4503-9213-6},
pages = {1660-1662},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
title = {Minimizing Expected Intrusion Detection Time in Adversarial Patrolling},
url = {https://www.ifaamas.org/Proceedings/aamas2022/pdfs/p1660.pdf},
year = {2022}
}
TY - JOUR
ID - 2214539
AU - Klaška, David - Kučera, Antonín - Musil, Vít - Řehák, Vojtěch
PY - 2022
TI - Minimizing Expected Intrusion Detection Time in Adversarial Patrolling
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
CY - Neuveden
SN - 9781450392136
KW - Security Games
KW - Adversarial Patrolling
UR - https://www.ifaamas.org/Proceedings/aamas2022/pdfs/p1660.pdf
N2 - In adversarial patrolling games, a mobile Defender strives to discover intrusions at vulnerable targets initiated by an Attacker. The Attacker’s utility is traditionally defined as the probability of completing an attack, possibly weighted by target costs. However, in many real-world scenarios, the actual damage caused by the Attacker depends on the time elapsed since the attack’s initiation to its detection. We introduce a formal model for such scenarios, and we show that the Defender always has an optimal strategy achieving maximal protection. We also prove that finite-memory Defender’s strategies are sufficient for achieving protection arbitrarily close to the optimum. Then, we design an efficient strategy synthesis algorithm based on differentiable programming and gradient descent.We evaluate the efficiency of our method experimentally.
ER -
KLAŠKA, David, Antonín KUČERA, Vít MUSIL and Vojtěch ŘEHÁK. Minimizing Expected Intrusion Detection Time in Adversarial Patrolling. Online. In Piotr Faliszewski, Viviana Mascardi, Catherine Pelachaud, Matthew E. Taylor. \textit{21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022.}. Neuveden: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2022, p.~1660-1662. ISBN~978-1-4503-9213-6. Available from: https://dx.doi.org/10.5555/3535850.3536068.
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