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Online Learning Methods for Border Patrol Resource Allocation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00225027" target="_blank" >RIV/68407700:21230/14:00225027 - isvavai.cz</a>

  • Result on the web

    <a href="http://link.springer.com/chapter/10.1007/978-3-319-12601-2_20" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-12601-2_20</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-12601-2_20" target="_blank" >10.1007/978-3-319-12601-2_20</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Online Learning Methods for Border Patrol Resource Allocation

  • Original language description

    We introduce a model for border security resource allocation with repeated interactions between attackers and defenders. The defender must learn the optimal resource allocation strategy based on historical apprehension data, balancing exploration and exploitation in the policy. We experiment with several solution methods for this online learning problem including UCB, sliding-window UCB, and EXP3. We test the learning methods against several different classes of attackers including attacker with randomly varying strategies and attackers who react adversarially to the defender's strategy. We present experimental data to identify the optimal parameter settings for these algorithms and compare the algorithms against the different types of attackers.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Others

  • Publication year

    2014

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Decision and Game Theory for Security

  • ISBN

    978-3-319-12600-5

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

    340-349

  • Publisher name

    Springer

  • Place of publication

    Heidelberg

  • Event location

    Los Angeles

  • Event date

    Nov 6, 2014

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000345594300020