| KLAŠKA, David, Antonín KUČERA, Vojtěch ŘEHÁK a Vít MUSIL. Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games. Online. In de Campos, Cassio and Maathuis, Marloes H. Proceedings of 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021). Neuveden: AUAI Press, 2021, s. 471-481. ISSN 2640-3498. |
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@inproceedings{1797259,
author = {Klaška, David and Kučera, Antonín and Řehák, Vojtěch and Musil, Vít},
address = {Neuveden},
booktitle = {Proceedings of 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021)},
editor = {de Campos, Cassio and Maathuis, Marloes H.},
keywords = {adversarial security games; strategy synthesis},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Neuveden},
pages = {471-481},
publisher = {AUAI Press},
title = {Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games},
url = {https://proceedings.mlr.press/v161/klaska21a.html},
year = {2021}
}
TY - JOUR
ID - 1797259
AU - Klaška, David - Kučera, Antonín - Řehák, Vojtěch - Musil, Vít
PY - 2021
TI - Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games
PB - AUAI Press
CY - Neuveden
KW - adversarial security games
KW - strategy synthesis
UR - https://proceedings.mlr.press/v161/klaska21a.html
N2 - We design a new efficient strategy synthesis method applicable to adversarial patrolling problems on graphs with arbitrary-length edges and possibly imperfect intrusion detection. The core ingredient is an efficient algorithm for computing the value and the gradient of a function assigning to every strategy its "protection" achieved. This allows for designing an efficient strategy improvement algorithm by differentiable programming and optimization techniques. Our method is the first one applicable to real-world patrolling graphs of reasonable sizes. It outperforms the state-of-the-art strategy synthesis algorithm by a margin.
ER -
KLAŠKA, David, Antonín KUČERA, Vojtěch ŘEHÁK a Vít MUSIL. Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games. Online. In de Campos, Cassio and Maathuis, Marloes H. \textit{Proceedings of 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021)}. Neuveden: AUAI Press, 2021, s.~471-481. ISSN~2640-3498.
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