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Endomorphisms of Classical Planning Tasks

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00350200" target="_blank" >RIV/68407700:21230/21:00350200 - isvavai.cz</a>

  • Result on the web

    <a href="https://ojs.aaai.org/index.php/AAAI/article/view/17406" target="_blank" >https://ojs.aaai.org/index.php/AAAI/article/view/17406</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Endomorphisms of Classical Planning Tasks

  • Original language description

    Detection of redundant operators that can be safely removed from the planning task is an essential technique allowing to greatly improve performance of planners. In this paper, we employ structure-preserving maps on labelled transition systems (LTSs), namely endomorphisms well known from model theory, in order to detect redundancy. Computing endomorphisms of an LTS induced by a planning task is typically infeasible, so we show how to compute some of them on concise representations of planning tasks such as finite domain representations and factored LTSs. We formulate the computation of endomorphisms as a constraint satisfaction problem (CSP) that can be solved by an off-the-shelf CSP solver. Finally, we experimentally verify that the proposed method can find a sizeable number of redundant operators on the standard benchmark set.

  • 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/GJ18-24965Y" target="_blank" >GJ18-24965Y: Privacy Preserving Multi-agent Planning</a><br>

  • Continuities

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

Others

  • Publication year

    2021

  • 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-Fifth AAAI Conference on Artificial Intelligence

  • ISBN

    978-1-57735-866-4

  • ISSN

  • e-ISSN

    2374-3468

  • Number of pages

    9

  • Pages from-to

    11835-11843

  • Publisher name

    Association for the Advancement of Artificial Intelligence (AAAI)

  • Place of publication

    Palo Alto, California

  • Event location

    Virtual Conference

  • Event date

    Feb 2, 2021

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000681269803058