Neural Approaches to Machine Consciousness.

‘Machine Consciousness’, which some years ago might have been suppressed as an inappropriate pursuit, has come out of the closet and is now a legitimate area of research concern. This paper briefly surveys the last few years of worldwide research in this area which divides into rule-based and neural approaches and then reviews the work of the author’s laboratory during the last ten years. The paper develops a fresh perspective on this work: it is argued that neural approaches, in this case, digital neural systems, can address phenomenological consciousness. Important clarifications of phenomenology and virtuality which enter this modelling are explained in the early parts of the paper. In neural models, phenomenology is a form of depictive inner representation that has five specific axiomatic features: a sense of self-presence in an external world; a sense of imagination of past experience and fiction; a sense of attention; a capacity for planning; a sense of emotion-based volition that influences planning. It is shown that these five features have separate but integrated support in dynamic neural systems. [ABSTRACT FROM AUTHOR]