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@inproceedings{1408461,
author = {Klaška, David and Kučera, Antonín and Lamser, Tomáš and Řehák, Vojtěch},
address = {Richland, SC},
booktitle = {Proceedings of the 2018 International Conference on Autonomous Agents & Multiagent Systems},
doi = {http://dx.doi.org/10.5555/3237383.3237481},
keywords = {patrolling games; single and multi-agent planning and scheduling},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Richland, SC},
isbn = {978-1-5108-6808-3},
pages = {659-666},
publisher = {International Foundation for Autonomous Agents and Multiagent Systems},
title = {Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games},
url = {http://dl.acm.org/citation.cfm?id=3237383.3237481},
year = {2018}
}
TY - JOUR
ID - 1408461
AU - Klaška, David - Kučera, Antonín - Lamser, Tomáš - Řehák, Vojtěch
PY - 2018
TI - Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games
PB - International Foundation for Autonomous Agents and Multiagent Systems
CY - Richland, SC
SN - 9781510868083
KW - patrolling games
KW - single and multi-agent planning and scheduling
UR - http://dl.acm.org/citation.cfm?id=3237383.3237481
L2 - http://dl.acm.org/citation.cfm?id=3237383.3237481
N2 - We give a polynomial-time algorithm for synthesizing efficient regular strategies in adversarial patrolling games with general topology. Regular strategies use finite memory to gather some relevant information about the history of Defender's moves which results in substantially better protection of the targets. So far, the scope of automatic strategy synthesis was limited to positional strategies (which ignore the history) or to regular strategies where the underlying finite-memory observer had to be supplied manually. Furthermore, the existing methods do not give any information on how far are the constructed strategies from being optimal. In this paper, we try to overcome these limitations. We develop a novel gradient-based algorithm for synthesizing regular strategies where the underlying finite-memory observers are constructed algorithmically. The running time of our algorithm is polynomial which makes the algorithm applicable to instances of realistic size. Furthermore, we develop an algorithm for computing an upper bound on the best achievable protection, and compare the quality of the constructed strategies against this bound. Thus, we can effectively measure the "distance'' of the constructed strategies from optimal strategies, and our experiments show that this distance is often quite small.
ER -
KLAŠKA, David, Antonín KUČERA, Tomáš LAMSER and Vojtěch ŘEHÁK. Automatic Synthesis of Efficient Regular Strategies in Adversarial Patrolling Games. Online. In \textit{Proceedings of the 2018 International Conference on Autonomous Agents \&{} Multiagent Systems}. Richland, SC: International Foundation for Autonomous Agents and Multiagent Systems, 2018. p.~659-666. ISBN~978-1-5108-6808-3. Available from: https://dx.doi.org/10.5555/3237383.3237481. [citováno 2024-04-23]
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