Tomas Veloz, Francis Heylighen, and Olaf Witkowski

Entropy 2023, 25(2), 286

Understanding the underlying structure of evolutionary processes is one the most important issues of scientific enquiry of this century. In the twentieth century, scientific thinking witnessed the overwhelming power of the evolutionary paradigm. It not only solidified the foundations of diverse areas, such as cell-biology, ecology, and economics, but also fostered the development of novel mathematical and computational tools to model and simulate how evolutionary processes take place.
In addition to the application of the evolutionary paradigm and the discovery of the evolutionary features for processes of diverse nature, there is another interesting aspect which touches upon the emergence of novel evolutionary processes. Namely, the emergence of an evolutionary process requires a complex transition between a prior form where no evolutionary process is undergoing and a posterior form where the evolutionary process has been triggered.
Theoretical methods to describe the emergence of evolutionary processes require the consideration of complex systemic notions, such as self-organization, resilience, contextuality, among others. Therefore, complexity and evolution became intertwined notions: evolution not only leads to but also depends on the development of increasingly complex forms and functions.
In this Special Issue, we put together eight articles, mostly of interdisciplinary nature, that explore from recent advances in the modeling of complex systems, as well as of the increasing modeling power and growth of databases associated to evolutionary processes.

Read the full article at: www.mdpi.com

Francis Heylighen 

Foundations of Science volume 28, pages 85–107 (2023)

Quantum phenomena are notoriously difficult to grasp. The present paper first reviews the most important quantum concepts in a non-technical manner: superposition, uncertainty, collapse of the wave function, entanglement and non-locality. It then tries to clarify these concepts by examining their analogues in complex, self-organizing systems. These include bifurcations, attractors, emergent constraints, order parameters and non-local correlations. They are illustrated with concrete examples that include Rayleigh–Bénard convection, social self-organization and Gestalt perception of ambiguous figures. In both cases, quantum and self-organizing, the core process appears to be a symmetry breaking that irreversibly and unpredictably “collapses” an ambiguous state into one of a number of initially equivalent “eigenstates” or “attractors”. Some speculations are proposed about the non-linear amplification of quantum fluctuations of the vacuum being ultimately responsible for such symmetry breaking.

Read the full article at: link.springer.com

Tom Froese, Natalya Weber, Ivan Shpurov, Takashi Ikegami

The theory of autopoiesis has been influential in many areas of theoretical biology, especially in the fields of artificial life and origins of life. However, it has not managed to productively connect with mainstream biology, partly for theoretical reasons, but arguably mainly because deriving specific working hypotheses has been challenging. The theory has recently undergone significant conceptual development in the enactive approach to life and mind. Hidden complexity in the original conception of autopoiesis has been explicated in the service of other operationalizable concepts related to self-individuation: precariousness, adaptivity, and agency. Here we advance these developments by highlighting the interplay of these concepts with considerations from thermodynamics: reversibility, irreversibility, and path-dependence. We interpret this interplay in terms of the self-optimization model, and present modeling results that illustrate how these minimal conditions enable a system to re-organize itself such that it tends toward coordinated constraint satisfaction at the system level. Although the model is still very abstract, these results point in a direction where the enactive approach could productively connect with cell biology.

Read the full article at: www.biorxiv.org

Martin Arvidsson, Niclas Lovsjö & Marc Keuschnigg 
Nature Human Behaviour (2023)

Theories of urban scaling have demonstrated remarkable predictive accuracy at aggregate levels. However, they have overlooked the stark inequalities that exist within cities. Human networking and productivity exhibit heavy-tailed distributions, with some individuals contributing disproportionately to city totals. Here we use micro-level data from Europe and the United States on interconnectivity, productivity and innovation in cities. We find that the tails of within-city distributions and their growth by city size account for 36–80% of previously reported scaling effects, and 56–87% of the variance in scaling between indicators of varying economic complexity. Providing explanatory depth to these findings, we identify a mechanism—city size-dependent cumulative advantage—that constitutes an important channel through which differences in the size of tails emerge. Our findings demonstrate that urban scaling is in large part a story about inequality in cities, implying that the causal processes underlying the heavier tails in larger cities must be considered in explanations of urban scaling. This result also shows that agglomeration effects benefit urban elites the most, with the majority of city dwellers partially excluded from the socio-economic benefits of growing cities.

Read the full article at: www.nature.com