On-the-fly Adaptation of Patrolling Strategies in Changing Environments
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00127027" target="_blank" >RIV/00216224:14330/22:00127027 - isvavai.cz</a>
Result on the web
<a href="https://proceedings.mlr.press/v180/brazdil22a.html" target="_blank" >https://proceedings.mlr.press/v180/brazdil22a.html</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
On-the-fly Adaptation of Patrolling Strategies in Changing Environments
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF18_053%2F0016952" target="_blank" >EF18_053/0016952: Postdoc2MUNI</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, UAI 2022
ISBN
9781713863298
ISSN
2640-3498
e-ISSN
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Number of pages
11
Pages from-to
244-254
Publisher name
Proceedings of Machine Learning Research
Place of publication
Neuveden
Event location
Eindhoven, Netherlands
Event date
Aug 1, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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