Representational systems

Minds and Machines 20 (1):69-101 (2010)
Abstract
The concept of representation has been a key element in the scientific study of mental processes, ever since such studies commenced. However, usage of the term has been all but too liberal—if one were to adhere to common use it remains unclear if there are examples of physical systems which cannot be construed in terms of representation. The problem is considered afresh, taking as the starting point the notion of activity spaces—spaces of spatiotemporal events produced by dynamical systems. It is argued that representation can be analyzed in terms of the geometrical and topological properties of such spaces. Several attributes and processes associated with conceptual domains, such as logical structure, generalization and learning are considered, and given analogues in structural facets of activity spaces, as are misrepresentation and states of arousal. Based on this analysis, representational systems are defined, as is a key concept associated with such systems, the notion of representational capacity. According to the proposed theory, rather than being an all or none phenomenon, representation is in fact a matter of degree—that is can be associated with measurable quantities, as is behooving of a putative naturalistic construct.
Keywords Computation and mind   Computational neuroscience   Conceptual representation   Curvature   Geometry   Homology   Isomorphism   Learning   Misrepresentation   Persistent homology   Representation   Representational capacity   Similarity   States of consciousness   Topology
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References found in this work BETA
Mark H. Bickhard (1993). Representational Content in Humans and Machines. Journal of Experimental and Theoretical Artificial Intelligence 5:285-33.
Shimon Edelman (2008). On the Nature of Minds, Or: Truth and Consequences. Journal of Experimental and Theoretical Ai 20:181-196.

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