Complexes

A month late, but I share a draft where we propose a simple measure of antifragility and apply it to random and biological Boolean networks. Spoiler: biological networks are antifragile. Abstract: Antifragility is a property that enhances the capability of a system in response to external perturbations. Although the concept has been applied in many areas, a practical measure of antifragility has not been developed yet. Here we propose a simply calculable measure of antifragility, based on the change of "satisfaction" before and after adding perturbations, and apply it to random Boolean networks (RBNs). Using the measure, we found that ordered RBNs are the most antifragile. Also, we demonstrate that seven biological systems are antifragile. Our measure and results can be used in various applications of Boolean networks (BNs) including creating antifragile engineering systems, identifying the genetic mechanism of antifragile biological systems, and developing new treatment st...

We present a set of Matlab/Octave functions to compute measures of emergence, self-organization, and complexity applied to discrete and continuous data. These measures are based on Shannon’s information and differential entropy. Examples from different datasets and probability distributions are provided to show how to use our proposed code. Santamaría-Bonfil, G., Gershenson, C. & Fernández, N. (2017). A package for measuring emergence, self-organization, and complexity based on Shannon entropy. Frontiers in Robotics and AI , 4 :10. http://journal.frontiersin.org/article/10.3389/frobt.2017.00010/full

Highlights • The useful of quantitative indicators of ecological complexity is evaluated. • Chaos should not be confused with complexity. • Light and temperature cause different ranges of complexity in the gradient. • Homoeostasis variation is related to the seasonal changes and transitions. • Autopoiesis reveals groups with higher and lower degree of autonomy. Abstract Measuring complexity is fast becoming a key instrument to compare different ecosystems at various scales in ecology. To date there has been little agreement on how to properly describe complexity in terms of ecology. In this regard, this manuscript assesses the significance of using a set of proposed measures based on information theory. These measures are as follows: emergence, self-organization, complexity, homeostasis and autopoiesis. A combination of quantitative and qualitative approaches was used in the data analysis with the aim to apply these proposed measures. This study system...

The morphology of urban agglomeration is studied here in the context of information exchange between different spatio-temporal scales. Urban migration to and from cities is characterised as non-random and following non-random pathways. Cities are multidimensional non-linear phenomena, so understanding the relationships and connectivity between scales is important in determining how the interplay of local/regional urban policies may affect the distribution of urban settlements. In order to quantify these relationships, we follow an information theoretic approach using the concept of Transfer Entropy. Our analysis is based on a stochastic urban fractal model, which mimics urban growing settlements and migration waves. The results indicate how different policies could affect urban morphology in terms of the information generated across geographical scales. Murcio R, Morphet R, Gershenson C, Batty M (2015) Urban Transfer Entropy across Scales. PLoS ONE 10(7): e0133780. doi:10.1371/journ...

Self-organisation occurs in natural phenomena when a spontaneous increase inorder is produced by the interactions of elements of a complex system. Thermodynamically,this increase must be offset by production of entropy which, broadly speaking, can beunderstood as a decrease in order. Ideally, self-organisation can be used to guide the systemtowards a desired regime or state, while “exporting” the entropy to the system’s exterior. Thus, Guided Self-Organisation (GSO) attempts to harness the order-inducing potentialof self-organisation for specific purposes. Not surprisingly, general methods developed tostudy entropy can also be applied to guided self-organisation. This special issue covers a broad diversity of GSO approaches which can be classified in three categories: informationtheory, intelligent agents, and collective behavior. The proposals make another step towardsa unifying theory of GSO which promises to impact numerous research fields. Entropy Methods in Guided Self-Organisat...