AMIA: A knowledge representation model for computational autobiographic agents

W.C. Ho, S. Watson, K. Dautenhahn

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

    4 Citations (Scopus)
    47 Downloads (Pure)


    This paper describes a hierarchical design for knowledge representation in computational autobiographic memory. This model is named AMIA (Autobiographic Memory for Intelligent Agents). Inspired by research in human autobiographic memory from the areas of Psychology and Cognitive Science, the self memory system (SMS) is modelled as 1) the general knowledge structure of agents’ significant events and 2) the unique “self” that SMS creates for an individual agent. We first carry out a concentrated review of autobiographic memory, emotion and event, and how they relate to each other. For AMIA, we start with an overview for different levels of the overall organisation and interactions between levels. We then focus on the design at the bottom level of AMIA – Action and Event levels. We also discuss the role of general event representations (GERs) which create knowledge representations for routine and highly expected events to be understood by autonomous agents, in conjunction with support from the autobiographic knowledge base in the reconstruction process of autobiographic events. Finally, we discuss the possible agent implementations for future research directions.
    Original languageEnglish
    Title of host publicationIn: Procs of IEEE 6th Int Conf on Development and Learning 2007 (ICDL 2007)
    PublisherInstitute of Electrical and Electronics Engineers (IEEE)
    ISBN (Print)978-1-4244-1116-0
    Publication statusPublished - 2007


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