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Regular Strategies and Strategy Improvement: Efficient Tools for Solving Large Patrolling Problems

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00088484" target="_blank" >RIV/00216224:14330/16:00088484 - isvavai.cz</a>

  • Result on the web

    <a href="http://dl.acm.org/citation.cfm?id=2937095" target="_blank" >http://dl.acm.org/citation.cfm?id=2937095</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Regular Strategies and Strategy Improvement: Efficient Tools for Solving Large Patrolling Problems

  • Original language description

    In patrolling problems, the task is to compute an optimal strategy for a patroller who moves among vulnerable targets and aims at detecting possible intrusions. Previous approaches to this problem utilize non-linear programming to synthesize (sub)optimal patroller's strategies, which has a negative impact on their scalability. Further, the solution space is usually restricted to positional strategies or to strategies dependent on a bounded history of patroller's moves. In this paper we introduce regular strategies that utilize deterministic finite-state automata to collect some information about the whole history of patroller's moves, and show that regular strategies are strictly more powerful than strategies dependent on a bounded history. Further, we design a strategy improvement technique for regular strategies which completely avoids solving large non-linear programs.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA15-17564S" target="_blank" >GA15-17564S: Game Theory in Formal Analysis and Verification of Computer Systems</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2016

  • 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 2016 International Conference on Autonomous Agents & Multiagent Systems

  • ISBN

    9781450342391

  • ISSN

    1548-8403

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    1171-1179

  • Publisher name

    ACM

  • Place of publication

    New York

  • Event location

    Singapore

  • Event date

    May 9, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article