Abstract
In this book, the main improvement on Grassberger’s original definition of the effective measure complexity EMC, which is based on classic information-theoretic quantities like Shannon’s information entropy that were developed to evaluate stochastic processes with discrete states, is the generalization of the theory and measures to continuous-state processes like that generated by the previously introduced VAR(1) model of cooperative work according to state Eq. 8. However, Li and Xie (1996), Bialek et al. (2001), de Cock (2002), Bialek (2003), Ellison et al. (2009) and others have already pioneered the generalization of Grassberger’s concepts toward continuous systems in their works, and we can build upon their results. Their analyses show that we must primarily consider the so-called “differential block entropy” (Eq. 233) and the corresponding continuous-type mutual information (Eq. 234) as basic information-theoretic quantities.
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Schlick, C., Demissie, B. (2016). Model-Driven Evaluation of the Emergent Complexity of Cooperative Work Based on Effective Measure Complexity. In: Product Development Projects. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-21717-8_4
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