Characterising the Difference between Complex Adaptive and Conventional Combat Models
M. K. Lauren

TL;DR
This paper compares complex adaptive combat models with conventional ones, showing that adaptive models exhibit turbulent, non-linear dynamics with properties like clustering and fat-tailed distributions, which are not captured by traditional methods.
Contribution
It introduces a cellular automaton model to demonstrate the non-linear, turbulent behavior of complex adaptive combat systems and highlights the limitations of conventional statistical analysis.
Findings
Complex adaptive models show turbulent dynamics and non-linear attrition functions.
Fat-tailed distributions and clustering are observed in casualty data.
A transition between two states resembles fluid turbulence phenomena.
Abstract
An attempt is made to quantitatively demonstrate the difference between a complex adaptive combat model and conventional combat models. The work shows that complex adaptive models may give rise to "turbulent" dynamics, which emerge once the battlefield is no longer "linear", i.e. once military formations no longer form ordered lines or columns. This is done using a cellular automaton model. This model exhibits a high degree of complexity, leading to a rich variety of behaviour. Conventional statistical methods fail to adequately capture this richness. Particular attention is paid to the properties of the attrition function. It is found that this function is discontinuous and possesses non-linear properties such as clustering of casualties, scaling of the statistical moments of the data and fat-tailed probability distributions. Fractal methods are found to be capable of quantifying these…
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Taxonomy
TopicsChaos control and synchronization · Mathematical and Theoretical Epidemiology and Ecology Models · Statistical Mechanics and Entropy
