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.


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.



Parallel distributed computing within interconnected nets.

A system also can be understood as a net of simple components with propagation of flows.

E. ANDREEWSKY explains: "According to Connectionism, the brain and its neurons explain behavior, and the terms used in this field, such as neurons, synapses, activation, propagation, suggest a biological explanation for cognitive phenomena. The former A.I. abstract symbolic representations become a set of very simple elements (formal neurons) functioning in parallel. Like the perceptron, connectionist systems work through learning & Connectionist systems do not have central units, and each of their elements functions in its local environment in order to determine a global cooperation, that is the system's organization. The network shapes itself progressively with the stimuli it receives; in other words, its learning activity, which is continuous during its implementation, results in changes of the network itself (whereas classically, learning is only change in knowledge representation)" (1993, p.192-193).

Of course "change in knowledge representation" implies the previous existence of knowledge. Thus such a view of learning does not explain the genesis, or better, the autogenesis of knowledge.

The physio-psychological version of connectionism is an extension of D. RUMELHART, J. McCLELLAND and G. HINTON's Parallel Distributed Processing, which is a model for information processing.

As to the mechanism of connectionist construction, E. ANDREEWSKY resumes J. Mc CLELLAND and D. RUMELHART explanations: "The communication between the different units of this system no longer takes place by means of messages as in classical Artificial Intelligence, but through activation values: numbers and not symbols. The interpretation of the operation is no longer obtained in terms of messages transmited between modules of the system; it represents the activated states of the whole system" (p.193).

Morevover, and in accordance with D. HEBB's reinforcement through repeated stimulation, connectionism implies reinforcement of pathways by frequent use.

Connectionism is also obviously and closely related to the more general problem of autogenesis in living and in social systems.

Connectionist network: "A parallel-processing system made of many simple computational units, linked (as brain-cells are) by excitatory or inhibitory connections" (M. BODEN, 1990, p.124).

This author explains: "One unit modifies another's activity to different degrees, dependent on the relevant connection-weight (expressed as a number between plus-one and minusone). The details of these weight changes are governed by differential equations, like those used in physics. A concept is represented as a "stable activity-pattern across the entire system".

"In networks that can learn, the connection weights are continually adjusted to maximize the probability of reaching equilibrium. Connections used often are strengthened, and if two units are activated simultaneously, then connection weights are adjusted to make this more likely in the future" (Ibid).

Moreover: "The larger the network, and the more distinct the patterns, the more associations can be learnt" (Ibid).

→; Algorithm (Back propagation)


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


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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