Crisis‐driven evolutionary learning: conceptual foundations and systemic modelling ‐ a summary abstract

Michael P. Byron (Department of Politics and Society, University of California, Irvine, USA)

Kybernetes

ISSN: 0368-492X

Publication date: 1 August 1997

Abstract

Evaluates the hypothesis that the real‐world political system constitutes a complex adaptive learning system. Abstracts relevant parameters of this system to create a computer model, which is utilized to generate data for a singular predictive instance (SPI) of systemic learning: warfare frequencies. Compares these data with corresponding real‐world empirical data for this SPI. A finding that the two sets of data are closely correlated allows for extrapolation of model systemic findings to the real‐world system. Discovers that the data support the hypothesis that the real‐world system is, indeed, a complex adaptive learning system.

Keywords

Citation

Byron, M. (1997), "Crisis‐driven evolutionary learning: conceptual foundations and systemic modelling ‐ a summary abstract", Kybernetes, Vol. 26 No. 6/7, pp. 716-724. https://doi.org/10.1108/03684929710169889

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Publisher

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MCB UP Ltd

Copyright © 1997, MCB UP Limited

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