Making sense of incomplete and conflicting narrative knowledge in the presence of abnormalities, unobservable processes, and other real world considerations is a challenge and crucial requirement for cognitive robotics systems. An added challenge, even when suitably specialised action languages and reasoning systems exist, is practical integration and application within large-scale robot control frameworks. In the backdrop of an autonomous wheelchair robot control task, we report on application-driven work to realise postdiction triggered abnormality detection and re-planning for real-time robot control: (a) Narrative-based knowledge about the environment is obtained via a larger smart environment framework; and (b) abnormalities are postdicted from stable-models of an answer-set program corresponding to the robot's epistemic model. The overall reasoning is performed in the context of an approximate epistemic action theory based planner implemented via a translation to answer-set programming. ; arXiv:1306.0665


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    Titel :

    Narrative based Postdictive Reasoning for Cognitive Robotics


    Beteiligte:
    Eppe, Manfred (Autor:in) / Bhatt, Mehul (Autor:in)

    Erscheinungsdatum :

    2013-01-01


    Medientyp :

    Paper


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



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