- December 2010
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The progress in the machine consciousness research fiel has to be assessed in terms of the features demonstrated by the new models and implementations currently being designed. In this paper, we focus on the
functional aspects of consciousness and propose the application of a
revision of ConsScale a biologically inspired scale for measuring
cognitive development in artificial agents in order to assess the
cognitive capabilities of machine consciousness implementations. We
argue that the progress in the implementation of consciousness in
artificial agents can be assessed by looking at how key cognitive
abilities associated to consciousness are integrated within artificial
systems. Specifically, we characterize ConsScale as a partially ordered
set and propose a particular dependency hierarchy for cognitive skills.
Associated to that hierarchy a graphical representation of the cognitive
profile of an artificial agent is presented as a helpful analytic tool.
The proposed evaluation schema is discussed and applied to a number of
significant machine consciousness models and implementations. Finally,
the possibility of generating qualia and phenomenological states in
machines is discussed in the context of the proposed analysis.