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Lexicographic Entailment, Syntax Splitting and the Drowning Problem

    Research output: Chapter in Book/Report/Conference proceedingConference Article in proceedingAcademicpeer-review

    Abstract

    Lexicographic inference is a well-known and popular approach to reasoning with non-monotonic conditionals. It is a logic of very high-quality, as it extends rational closure and avoids the so-called drowning problem. It seems, however, this high quality comes at a cost, as reasoning on the basis of lexicographic inference is of high computational complexity. In this paper, we show that lexicographic inference satisfies syntax splitting, which means that we can restrict our attention to parts of the belief base that share atoms with a given query, thus seriously restricting the computational costs for many concrete queries. Furthermore, we make some observations on the relationship between c-representations and lexicographic inference, and reflect on the relation between syntax splitting and the drowning problem.
    Original languageEnglish
    Title of host publicationProceedings of the Thirty-First International Joint Conference on Artificial Intelligence
    Editors Luc De Raedt
    PublisherInternational Joint Conferences on Artificial Intelligence
    Pages2662-2668
    Number of pages7
    ISBN (Electronic)978-1-956792-00-3
    DOIs
    Publication statusPublished - 23 Jul 2022
    EventThe Thirty-First International Joint Conference on Artificial Intelligence - Vienna University of Technology, Vienna, Austria
    Duration: 23 Jul 202229 Jul 2022
    Conference number: 31
    https://www.ijcai.org/proceedings/2022/

    Conference

    ConferenceThe Thirty-First International Joint Conference on Artificial Intelligence
    Abbreviated titleIJCAI-22
    Country/TerritoryAustria
    CityVienna
    Period23/07/2229/07/22
    Internet address

    Keywords

    • Knowledge Representation and Reasoning: Non-monotonic Reasoning

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