Deutsch Intern
    Chair of Computer Science VI - Artificial Intelligence and Applied Computer Science

    WLP 2020

    34th Workshop on (Constraint) Logic Programming

    The Workshop on Logic Programming (WLP 2020) will be held at the German Conference on Artificial Intelligence (KI 2020) in Bamberg


    Contributions are welcome on all theoretical, experimental, and application aspects of logic and constraint logic programming. The topics include, but are not limited to the following areas:

    • Logic and Constraint Logic Programming Languages and Extensions
    • Knowledge Representation and Non-monotonic Reasoning
    • Applications and Application Areas of (C)LP
    • Implementations

    Submission Guidelines

    The structure of the workshop will be informal. We invite extended abstracts (2-3 pages, using the Springer LNCS style) in the following categories:

    • Theoretical background
    • Applications
    • Novel approaches
    • Open research questions
    • System descriptions and demonstrations
    • Ongoing work

    Submission is via Easychair submission website for WLP 2020.
    All papers will be judged on the basis of significance, relevance, correctness, originality, and clarity.


    All abstracts accepted for presentation at the conference will be published in informal proceedings publicly available. All accepted contributions will be presented during the workshop. At least one author is expected to register for the workshop and present the paper.


    • Submission:                                    13.07.2020
    • Notification of Authors:                27.07.2020
    • Camera-ready Papers:                  10.08.2020
    • Conference & Workshops:           Monday, 21.09.2020

    Organizing Committee

    Michael Hanus   (University of Kiel, Germany)
    Sibylle Schwarz (HTWK Leipzig, Germany)
    Dietmar Seipel  (University of Würzburg, Germany)


    • 14:00 - 14:30
      Michael Hanus
      Can Logic Programming Be Liberated from Backtracking?
      Abstract: Logic programming is historically tight with Prolog and its back-
      tracking search strategy. The use of backtracking was justified by efficiency
      reasons when Prolog was invented and is still present, although the incom-
      pleteness of backtracking destroys the elegant connection of logic program-
      ming and the underlying Horn clause logic. Moreover, it causes difficulties
      to teach logic programming. In this paper we argue that this is no longer
      necessary if new implementation approaches are taken into account.
    • 14:30 - 15:00
      Emmanuelle-Anna Dietz, Sophia Meier and Sibylle Schwarz
      Logic Programming and Human Syllogistic Reasoning
      Abstract: The Problem of understanding human reasoning processes is still not
      being solved. In a meta-analysis by Khemlani and Johnson-Laird from
      2012, humans were asked to complete a syllogism by drawing a conclusion
      on two given syllogistic premises. When looking at the results of this
      study, two observations can be done: Humans do not reason classically
      logically correct and different humans draw different conclusions, i.e.
      the human reasoner does not exist. Nevertheless, we assume, that there
      are underlying assumptions, that might be done by humans
      while reasoning, the so-called cognitive principles. Given a pair of
      syllogistic premises, a set of cognitive principles is formalized as
      logic programming clauses and the respective model is computed under the
      Weak Completion Semantics (WCS). Then the resulting conclusion can be
      derived and the relevance of the underlying cognitive principles in
      syllogistic reasoning can be assessed by comparing the conclusion with
      the answers of the participants in the meta-analysis. So far, ten of
      such cognitive principles have been identified for modeling human
      syllogistic reasoning.
    • 15:00 - 15:30
      Daniel Weidner and Dietmar Seipel
      A Graphical User Interface for Demonstrating Features
      of the Deductive Database System DDBase in Python
      Abstract: The coupling of the logic programming language Swi Prolog
      and the object–oriented language Python has been proposed in our pre-
      vious work PyPlC. In this paper, we use Python and PyPlC to built
      a graphical user interface for parts of the deductive database system
      Currently, the standard graphical user interface Xpce is bundled with
      Swi Prolog on Linux, Mac, and Windows; but Xpce does not exist for
      Android – and, thus, especially for many mobile phones. Moreover, it
      is unclear to which extend Xpce will be updated and supported on the
      various platforms in the future.
      In any case, it is necessary to connect Prolog applications to new and
      popular programming languages such as Python or Java to attract users
      from outside the Prolog community.
      The GUI to DDBase is implemented in Python with calls to Prolog, but
      we do not have to pass many arguments between Prolog and Python.
      We also don’t need any backtracking of the Prolog calls. In particular,
      we want to display a directory tree for selecting and evaluating logic
      programs, show the logic programs in a window for a text editor, present
      derived results in another text window, and, finally, visualize dependency
      graphs for the logic programs.
    • 16:00 - 17:00