David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Minds and Machines 20 (1):69-101 (2010)
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.
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Citations of this work BETA
Tomer Fekete & Shimon Edelman (2011). Towards a Computational Theory of Experience. Consciousness and Cognition 20 (3):807-827.
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