Integration of abductive reasoning and constraint optimization in SCIFF

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP) share the feature to constrain the set of possible solutions to a program via integrity or CLP constraints. These two frameworks have been merged in works by various authors, which developed efficient abductive proof-procedures empowered with constraint satisfaction techniques. However, while almost all CLP languages provide algorithms for finding an optimal solution with respect to some objective function (and not justanysolution), the issue has received little attention in ALP. In this paper we show how optimisation meta-predicates can be included in abductive proof-procedures, achieving in this way a significant improvement to research and practical applications of abductive reasoning. In the paper, we give the declarative and operational semantics of an abductive proof-procedure that encloses constraint optimization meta-predicates, and we prove soundness in the three-valued completion semantics. In the proof-procedure, the abductive logic program can invoke optimisation meta-predicates, which can invoke abductive predicates, in a recursive way.
Original languageUnknown
Title of host publicationLecture Notes in Computer Science
EditorsPM Hill, DS Warren
Place of PublicationBerlin Heidelberg
PublisherSpringer-Verlag
Pages387-401
Volume5649
ISBN (Print)978-3-642-02845-8
DOIs
Publication statusPublished - 1 Jan 2009
Event25th International Conference on Logic Programming (ICLP 2009) -
Duration: 1 Jan 2009 → …

Conference

Conference25th International Conference on Logic Programming (ICLP 2009)
Period1/01/09 → …

Keywords

    Cite this

    Alberti, M. (2009). Integration of abductive reasoning and constraint optimization in SCIFF. In PM. Hill, & DS. Warren (Eds.), Lecture Notes in Computer Science (Vol. 5649, pp. 387-401). Berlin Heidelberg: Springer-Verlag. https://doi.org/10.1007/978-3-642-02846-5_32
    Alberti, Marco. / Integration of abductive reasoning and constraint optimization in SCIFF. Lecture Notes in Computer Science. editor / PM Hill ; DS Warren. Vol. 5649 Berlin Heidelberg : Springer-Verlag, 2009. pp. 387-401
    @inproceedings{8493b46a66204c9eb0fe2b06eccb399c,
    title = "Integration of abductive reasoning and constraint optimization in SCIFF",
    abstract = "Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP) share the feature to constrain the set of possible solutions to a program via integrity or CLP constraints. These two frameworks have been merged in works by various authors, which developed efficient abductive proof-procedures empowered with constraint satisfaction techniques. However, while almost all CLP languages provide algorithms for finding an optimal solution with respect to some objective function (and not justanysolution), the issue has received little attention in ALP. In this paper we show how optimisation meta-predicates can be included in abductive proof-procedures, achieving in this way a significant improvement to research and practical applications of abductive reasoning. In the paper, we give the declarative and operational semantics of an abductive proof-procedure that encloses constraint optimization meta-predicates, and we prove soundness in the three-valued completion semantics. In the proof-procedure, the abductive logic program can invoke optimisation meta-predicates, which can invoke abductive predicates, in a recursive way.",
    keywords = "Constraint Handling Rules, Constraint Logic Programming, Abductive Logic Programming, Constraint Optimization",
    author = "Marco Alberti",
    year = "2009",
    month = "1",
    day = "1",
    doi = "10.1007/978-3-642-02846-5_32",
    language = "Unknown",
    isbn = "978-3-642-02845-8",
    volume = "5649",
    pages = "387--401",
    editor = "PM Hill and DS Warren",
    booktitle = "Lecture Notes in Computer Science",
    publisher = "Springer-Verlag",

    }

    Alberti, M 2009, Integration of abductive reasoning and constraint optimization in SCIFF. in PM Hill & DS Warren (eds), Lecture Notes in Computer Science. vol. 5649, Springer-Verlag, Berlin Heidelberg, pp. 387-401, 25th International Conference on Logic Programming (ICLP 2009), 1/01/09. https://doi.org/10.1007/978-3-642-02846-5_32

    Integration of abductive reasoning and constraint optimization in SCIFF. / Alberti, Marco.

    Lecture Notes in Computer Science. ed. / PM Hill; DS Warren. Vol. 5649 Berlin Heidelberg : Springer-Verlag, 2009. p. 387-401.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    TY - GEN

    T1 - Integration of abductive reasoning and constraint optimization in SCIFF

    AU - Alberti, Marco

    PY - 2009/1/1

    Y1 - 2009/1/1

    N2 - Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP) share the feature to constrain the set of possible solutions to a program via integrity or CLP constraints. These two frameworks have been merged in works by various authors, which developed efficient abductive proof-procedures empowered with constraint satisfaction techniques. However, while almost all CLP languages provide algorithms for finding an optimal solution with respect to some objective function (and not justanysolution), the issue has received little attention in ALP. In this paper we show how optimisation meta-predicates can be included in abductive proof-procedures, achieving in this way a significant improvement to research and practical applications of abductive reasoning. In the paper, we give the declarative and operational semantics of an abductive proof-procedure that encloses constraint optimization meta-predicates, and we prove soundness in the three-valued completion semantics. In the proof-procedure, the abductive logic program can invoke optimisation meta-predicates, which can invoke abductive predicates, in a recursive way.

    AB - Abductive Logic Programming (ALP) and Constraint Logic Programming (CLP) share the feature to constrain the set of possible solutions to a program via integrity or CLP constraints. These two frameworks have been merged in works by various authors, which developed efficient abductive proof-procedures empowered with constraint satisfaction techniques. However, while almost all CLP languages provide algorithms for finding an optimal solution with respect to some objective function (and not justanysolution), the issue has received little attention in ALP. In this paper we show how optimisation meta-predicates can be included in abductive proof-procedures, achieving in this way a significant improvement to research and practical applications of abductive reasoning. In the paper, we give the declarative and operational semantics of an abductive proof-procedure that encloses constraint optimization meta-predicates, and we prove soundness in the three-valued completion semantics. In the proof-procedure, the abductive logic program can invoke optimisation meta-predicates, which can invoke abductive predicates, in a recursive way.

    KW - Constraint Handling Rules

    KW - Constraint Logic Programming

    KW - Abductive Logic Programming

    KW - Constraint Optimization

    U2 - 10.1007/978-3-642-02846-5_32

    DO - 10.1007/978-3-642-02846-5_32

    M3 - Conference contribution

    SN - 978-3-642-02845-8

    VL - 5649

    SP - 387

    EP - 401

    BT - Lecture Notes in Computer Science

    A2 - Hill, PM

    A2 - Warren, DS

    PB - Springer-Verlag

    CY - Berlin Heidelberg

    ER -

    Alberti M. Integration of abductive reasoning and constraint optimization in SCIFF. In Hill PM, Warren DS, editors, Lecture Notes in Computer Science. Vol. 5649. Berlin Heidelberg: Springer-Verlag. 2009. p. 387-401 https://doi.org/10.1007/978-3-642-02846-5_32