There are many developed theories and implemented arti ̄cial systems in the area of machine consciousness, while none has achieved that. For a possible approach, we are interested in implementing a system by integrating di®erent theories. Along this way, this paper proposes a model based on the global workspace theory and attention mechanism, and providing a fundamental framework for our future work. To examine this model, two experiments are conducted. The ̄rst one demonstrates the agent's ability to shift attention over multiple stimuli, which accounts for the dynamics of conscious content. Another experiment of simulations of attentional blink and lag-1 sparing, which are two well-studied e®ects in psychology and neuroscience of attention and consciousness, aims to justify the agent's compatibility with human brains. In summary, the main contributions of this paper are (1) Adaptation of the global workspace framework by separated workspace nodes, reducing unnecessary computation but retaining the potential of global availability; (2) Embedding attention mechanism into the global workspace framework as the competition mechanism for the consciousness access; (3) Proposing a synchronization mechanism in the global workspace for supporting lag-1 sparing effect, retaining the attentional blink effect.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    A Design of Global Workspace Model with Attention: Simulations of Attentional Blink and Lag-1 Sparing



    Erscheinungsdatum :

    2022-03-01



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



    Drivers’ Attention Assessment by Blink Rate Measurement from EEG Signals

    Affanni, Antonio / Najafi, Taraneh Aminosharieh | IEEE | 2022



    Project moon-blink

    TIBKAT | 1966


    Eye blink completeness detection

    Fogelton, Andrej / Benesova, Wanda | British Library Online Contents | 2018


    Eye blink completeness detection

    Fogelton, Andrej / Benesova, Wanda | British Library Online Contents | 2018