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Lifted Inference with Tree Axioms

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F23%3A00367818" target="_blank" >RIV/68407700:21230/23:00367818 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.artint.2023.103997" target="_blank" >https://doi.org/10.1016/j.artint.2023.103997</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.artint.2023.103997" target="_blank" >10.1016/j.artint.2023.103997</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Lifted Inference with Tree Axioms

  • Original language description

    We consider the problem of weighted first-order model counting (WFOMC): given a first-order sentence ϕ and domain size , determine the weighted sum of models of ϕ over the domain . Past work has shown that any sentence using at most two logical variables admits an algorithm for WFOMC that runs in time polynomial in the given domain size [1], [2]. The same property was later also shown to hold for , the two-variable fragment with counting quantifiers [3]. In this paper, we further expand this result to any sentence ϕ with the addition of a tree axiom, stating that some distinguished binary relation in ϕ forms a tree in the graph-theoretic sense.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • 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

    2023

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Artificial Intelligence

  • ISSN

    0004-3702

  • e-ISSN

    1872-7921

  • Volume of the periodical

    324

  • Issue of the periodical within the volume

    November

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    15

  • Pages from-to

  • UT code for WoS article

    001080001100001

  • EID of the result in the Scopus database

    2-s2.0-85169822848