BCSSS

International Encyclopedia of Systems and Cybernetics

2nd Edition, as published by Charles François 2004 Presented by the Bertalanffy Center for the Study of Systems Science Vienna for public access.

About

The International Encyclopedia of Systems and Cybernetics was first edited and published by the system scientist Charles François in 1997. The online version that is provided here was based on the 2nd edition in 2004. It was uploaded and gifted to the center by ASC president Michael Lissack in 2019; the BCSSS purchased the rights for the re-publication of this volume in 200?. In 2018, the original editor expressed his wish to pass on the stewardship over the maintenance and further development of the encyclopedia to the Bertalanffy Center. In the future, the BCSSS seeks to further develop the encyclopedia by open collaboration within the systems sciences. Until the center has found and been able to implement an adequate technical solution for this, the static website is made accessible for the benefit of public scholarship and education.

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LEARNING by normative feedback 1)

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In a net of biological neurons, the global capacity of the net results from the self-organization of neural connections under the effects of the inputs that they receive and transmit.

L. PERSONNAZ et al. state: "The principle of this self-organization is simple: The efficiency of any synapse is reinforced when the neurons that it connects have a tendency to be active or inactive simultaneously; in the opposite case it lessens" (1988, p.1364).

This effect is strengthened locally within the strongly connected net, by repeated feedbacks.

Learning seems to be the progressive dynamic stabilization of frames of reference within the more or less narrow limits of a repertoire of stored information, relevant within a kind of pre-imprinted but very general program, while the irrelevant data are not retained.

See for example N. S. CLAYTON about song learning in birds (1991, p.466-72).

It could be a progressive algorithmization of behaviors. The upbuilding of such algorithms could possibly be modelized through attractors.

These concepts are also relevant for the new forms of perceptrons (recognition of more or less well written or printed types, for example).

Categories

  • 1) General information
  • 2) Methodology or model
  • 3) Epistemology, ontology and semantics
  • 4) Human sciences
  • 5) Discipline oriented

Publisher

Bertalanffy Center for the Study of Systems Science(2020).

To cite this page, please use the following information:

Bertalanffy Center for the Study of Systems Science (2020). Title of the entry. In Charles François (Ed.), International Encyclopedia of Systems and Cybernetics (2). Retrieved from www.systemspedia.org/[full/url]

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