Le Peutrec, Stephane with Michele Courant, "Living Systems Dynamics: A New Approach for Knowledge Representation", 1994
ua435
In the perspective of formulizing abstractions as afundamental facet of cognition, we study knowledge in its relationship to thebiological substratum from which its outcomes. Our research is mainly founded on the works of F.J. Varela concerningthe autonomy of living systems (autopoiesis) and of S. Lupasco on antagonism.We show how autopoiesis brings a new enlightment upon knowledge, by turningrepresentation problems to organization problems and how the autopoieticdynamics of living systems leads to a new formulation of machine learning. By developing new internal dynamics, a systemdoes not learn to know its environment, but to adapt himself to it.It follows that modeling an autopoietic system requires to focus, no more onsharing of semantic universes between a system and its environment, but onstructural models producing behavioral regularities of the system in answer toenvironmental perturbations. Autopoiesisseems therefore more suited for developing adaptive and complex systems,especially when an exhaustive specification of the operating factors isprohibitive, as well as for providing a unified framework for modelingcognition. Moreover it provides aparadigmatic foundation to the design of massively parallel system.
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