The significance of far-from-equilibrium infrastructure and metabolism is that the normative aspect of representation emerges in (functional) contributions to the maintenance of far-from-equilibrium conditions. If the far-from-equilibrium conditions are “minimal”,
or of minimal importance, then so also are the normative aspects of function and representation. It is this normativity that is indirectly scaled by any scaling of the far-from- equilibrium status of the ‘body’ of the system involved. Function and representation are normative insofar as, and to the extent that, there is something that is ontologically at stake
in their ‘successful’ functioning (Christensen & Bickhard, 2002).
Self-reproducing and living systems? This brings up the last point I wish to make about biological foundations. Cognition, if this model is correct, requires far-from- equilibrium systems that are recursively self-maintenant, in perhaps very complex ways. There is nothing in the model, however, that requires that these systems be self-
reproducing. It is a matter of definition, then, whether it is required that they be living.
(Not all animals are capable of self-reproduction, not even all animals that are capable of
clear cognition: e.g., any sterile organism, be it insect, such as a bee, or mammal, or human.) The interactive model, then, suggests that designed systems could in principle be fully capable of function, representation, and cognition — but not with the architectural and
process resources available in computer or connectionist models.
The interactive model is a version of the dynamic systems approach, and of autonomous agent approaches (Bickhard & Terveen, 1995). Unlike other versions, however, interactivism neither argues against the usefulness of correspondence representations (Port & van Gelder, 1995), nor for the necessity of correspondence, informational, representations (Clark & Toribio, 1995). Instead, it argues against the
common underlying assumption that representation is correspondence — and it argues that function and representation emerge naturally in the evolution of dynamic autonomous biological agents, but that they emerge in a way that correspondence approaches cannot account for. Interactivism reconfigures our assumptions about the biological foundations for cognition, and, therefore, for Cognitive Science.
Beer, R. D. (1995). A Dynamical Systems Perspective on Agent-Environment
Interaction. Artificial Intelligence, 73(1/2), 173.
Bickhard, M. H. (1980). Cognition, Convention, and Communication. New York: Praeger Publishers.