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Operator Mutexes and Symmetries for Simplifying Planning Tasks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00332635" target="_blank" >RIV/68407700:21230/19:00332635 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1609/aaai.v33i01.33017586" target="_blank" >https://doi.org/10.1609/aaai.v33i01.33017586</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1609/aaai.v33i01.33017586" target="_blank" >10.1609/aaai.v33i01.33017586</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Operator Mutexes and Symmetries for Simplifying Planning Tasks

  • Original language description

    Simplifying classical planning tasks by removing operators while preserving at least one optimal solution can significantly enhance the performance of planners. In this paper, we introduce the notion of operator mutex, which is a set of operators that cannot all be part of the same (strongly) optimal plan. We propose four different methods for inference of operator mutexes and experimentally verify that they can be found in a sizable number of planning tasks. We show how operator mutexes can be used in combination with structural symmetries to safely remove operators from the planning task.

  • 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

    Result was created during the realization of more than one project. More information in the Projects tab.

  • 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

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    7586-7593

  • Publisher name

    AAAI Press

  • Place of publication

    Menlo Park

  • Event location

    Honolulu

  • Event date

    Jan 27, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000486572502015