This paper builds upon a cognitive model and a study of how people find faults in a simple device (Ritter & Bibby, 2008). This existing learning model, called Diag, was implemented in Soar and is based on the idea that learning consists of procedural, declarative, and episodic learning. Because Diag is implemented in a version of Soar that is no longer supported, an implementation in an up-to-date cognitive architecture is necessary to understand Soar and to model further aspects of this task. We maintained Diag’s basic structure while reimplementing it in a high-level behavior representation language, Herbal, that generates Soar models and can generate different variants quickly. This newly implemented model, called Diag-H, was validated by comparing its predictions to Diag and the existing data. As a result, it could be shown that Diag-H creates nearly the same results as Diag but also incorporates the advantages of Herbal.


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    Titel :

    Reimplementing a Diagrammatic Reasoning Model in Herbal


    Beteiligte:
    Friedrich, Maik (Autor:in) / Frank, Ritter (Autor:in)

    Kongress:

    2009 ; Manchester, Großbritannien


    Erscheinungsdatum :

    25.07.2009


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Deutsch




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