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.

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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 MACHINE 2)

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"A machine capable of performing certain actions even though the builders do not know algorithms for these actions" (P. DENNING, 1992a, p.14).

The learning machine constructs its own algorithm to perform the task.

DENNING explains that it does so by adjusting "internal parameters of an associative memory", as it registers successive examples "each consisting of an input and a corresponding ideal" (Ibid.).

He adds: "… the machine's internal structure can be represented by a set of rules telling it how to respond to given inputs".

Moreover: "After each action, the machine uses the resulting pay-off feedback to modify its rule set so that an effective behavior is reinforced or an ineffective behavior is dropped".

In this way "… a population of rules evolves over time and the rules producing the highest pay-offs come to dominate the population". Thus "Genetic algorithms are being used as the builders of programs inside learning machines" (Ibid).

In order to be able to perform a task, a learning machine needs thus an algorithm producing algorithms, i.e. a genetic algorithm. Such a meta-algorithm must by necessity be able to produce, experiment and select combinations of basic rules.

The concept apply also quite probably to natural learning machines.

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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