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.
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/10.1108/03684929710169889Download as .RIS
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