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@inproceedings{2227363,
author = {Brázdil, Tomáš and Klaška, David and Kučera, Antonín and Musil, Vít and Novotný, Petr and Řehák, Vojtěch},
address = {Neuveden},
booktitle = {Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022},
editor = {James Cussens, Kun Zhang},
keywords = {patrolling games; strategy synthesis},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Neuveden},
isbn = {978-1-7138-6329-8},
pages = {244-254},
publisher = {Proceedings of Machine Learning Research},
title = {On-the-fly Adaptation of Patrolling Strategies in Changing Environments},
url = {https://proceedings.mlr.press/v180/brazdil22a.html},
year = {2022}
}
TY - JOUR
ID - 2227363
AU - Brázdil, Tomáš - Klaška, David - Kučera, Antonín - Musil, Vít - Novotný, Petr - Řehák, Vojtěch
PY - 2022
TI - On-the-fly Adaptation of Patrolling Strategies in Changing Environments
PB - Proceedings of Machine Learning Research
CY - Neuveden
SN - 9781713863298
KW - patrolling games
KW - strategy synthesis
UR - https://proceedings.mlr.press/v180/brazdil22a.html
N2 - We consider the problem of efficient patrolling strategy adaptation in a changing environment where the topology of Defender’s moves and the importance of guarded targets change unpredictably. The Defender must instantly switch to a new strategy optimized for the new environment, not disrupting the ongoing patrolling task, and the new strategy must be computed promptly under all circumstances. Since strategy switching may cause unintended security risks compromising the achieved protection, our solution includes mechanisms for detecting and mitigating this problem. The efficiency of our framework is evaluated experimentally.
ER -
BRÁZDIL, Tomáš, David KLAŠKA, Antonín KUČERA, Vít MUSIL, Petr NOVOTNÝ a Vojtěch ŘEHÁK. On-the-fly Adaptation of Patrolling Strategies in Changing Environments. Online. In James Cussens, Kun Zhang. \textit{Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022}. Neuveden: Proceedings of Machine Learning Research, 2022, s.~244-254. ISBN~978-1-7138-6329-8.
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