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Solving Partially Observable Stochastic Games with Public Observations

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00329800" target="_blank" >RIV/68407700:21230/19:00329800 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1609/aaai.v33i01.33012029" target="_blank" >http://dx.doi.org/10.1609/aaai.v33i01.33012029</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1609/aaai.v33i01.33012029" target="_blank" >10.1609/aaai.v33i01.33012029</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Solving Partially Observable Stochastic Games with Public Observations

  • Original language description

    n many real-world problems, there is a dynamic interactionbetween competitive agents. Partially observable stochasticgames (POSGs) are among the most general formal mod-els that capture such dynamic scenarios. The model capturesstochastic events, partial information of players about the en-vironment, and the scenario does not have a fixed horizon.Solving POSGs in the most general setting is intractable.Therefore, the research has been focused on subclasses ofPOSGs that have a value of the game and admit designing(approximate) optimal algorithms. We propose such a sub-class for two-player zero-sum games with discounted-sumobjective function—POSGs withpublic observations(PO-POSGs)—where each player is able to reconstruct beliefs ofthe other player over the unobserved states. Our results in-clude: (1) theoretical analysis of PO-POSGs and their valuefunctions showing convexity (concavity) in beliefs of maxi-mizing (minimizing) player, (2) a novel algorithm for approx-imating the value of the game, and (3) a practical demon-stration of scalability of our algorithm. Experimental resultsshow that our algorithm can closely approximate the value ofnon-trivial games with hundreds of states

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>

  • Continuities

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

Others

  • Publication year

    2019

  • 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-Third AAAI Conference on Artificial Intelligence

  • ISBN

    978-1-57735-809-1

  • ISSN

    2159-5399

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    2029-2036

  • Publisher name

    AAAI Press

  • Place of publication

    Menlo Park, California

  • Event location

    Honolulu

  • Event date

    Jan 27, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000485292602006