Minimizing Expected Intrusion Detection Time in Adversarial Patrolling
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00126563" target="_blank" >RIV/00216224:14330/22:00126563 - isvavai.cz</a>
Result on the web
<a href="https://www.ifaamas.org/Proceedings/aamas2022/pdfs/p1660.pdf" target="_blank" >https://www.ifaamas.org/Proceedings/aamas2022/pdfs/p1660.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5555/3535850.3536068" target="_blank" >10.5555/3535850.3536068</a>
Alternative languages
Result language
angličtina
Original language name
Minimizing Expected Intrusion Detection Time in Adversarial Patrolling
Original language description
In adversarial patrolling games, a mobile Defender strives to discover intrusions at vulnerable targets initiated by an Attacker. The Attacker’s utility is traditionally defined as the probability of completing an attack, possibly weighted by target costs. However, in many real-world scenarios, the actual damage caused by the Attacker depends on the time elapsed since the attack’s initiation to its detection. We introduce a formal model for such scenarios, and we show that the Defender always has an optimal strategy achieving maximal protection. We also prove that finite-memory Defender’s strategies are sufficient for achieving protection arbitrarily close to the optimum. Then, we design an efficient strategy synthesis algorithm based on differentiable programming and gradient descent.We evaluate the efficiency of our method 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
21st International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2022.
ISBN
9781450392136
ISSN
1548-8403
e-ISSN
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Number of pages
3
Pages from-to
1660-1662
Publisher name
International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Place of publication
Neuveden
Event location
Auckland, New Zealand
Event date
May 9, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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