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@inproceedings{1185661,
author = {Abaffy, Michal and Brázdil, Tomáš and Řehák, Vojtěch and Bošanský, Branislav and Kučera, Antonín and Krčál, Jan},
address = {Richland, SC, USA},
booktitle = {Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'14)},
editor = {Alessio Lomuscio, Paul Scerri, Ana Bazzan, and Michael Huhns},
keywords = {patrolling games; stochastic games; epsilon-optimal strategy},
howpublished = {paměťový nosič},
language = {eng},
location = {Richland, SC, USA},
isbn = {978-1-4503-2738-1},
pages = {1617-1618},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)},
title = {Solving adversarial patrolling games with bounded error: (extended abstract)},
year = {2014}
}
TY - JOUR
ID - 1185661
AU - Abaffy, Michal - Brázdil, Tomáš - Řehák, Vojtěch - Bošanský, Branislav - Kučera, Antonín - Krčál, Jan
PY - 2014
TI - Solving adversarial patrolling games with bounded error: (extended abstract)
PB - International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
CY - Richland, SC, USA
SN - 9781450327381
KW - patrolling games
KW - stochastic games
KW - epsilon-optimal strategy
N2 - Patrolling games are partially observable games played by two players, the defender and the attacker. The defender aims for detecting intrusions into vulnerable targets by following randomized routes among them, the attacker strives to maximize the probability of a successful (undetected) intrusion. We show how to translate patrolling games into turn-based perfect information stochastic games with safety objectives so that optimal strategies in the perfect information games can be transferred back to patrolling games. We design, to the best of our knowledge, the best algorithm which can compute an epsilon-optimal strategy for the defender among all (history-dependent) strategies.
ER -
ABAFFY, Michal, Tomáš BRÁZDIL, Vojtěch ŘEHÁK, Branislav BOŠANSKÝ, Antonín KUČERA a Jan KRČÁL. Solving adversarial patrolling games with bounded error: (extended abstract). In Alessio Lomuscio, Paul Scerri, Ana Bazzan, and Michael Huhns. \textit{Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems (AAMAS'14)}. Richland, SC, USA: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), 2014, s.~1617-1618. ISBN~978-1-4503-2738-1.
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