Journal launched: Frontiers in Complex Systems

Frontiers in Complex Systems publishes rigorously peer-reviewed quantitative research on Complex Systems, either theoretical, experimental, mathematical, computational or data description. Field Chief Editor Maxi San Miguel at the Institute for Cross-Disciplinary Physics and Complex Systems (IFISC) in Spain is supported by an outstanding Editorial Board of international experts. This open-access journal is to become the reference and natural publication outlet for the Complex Systems community at large, and to be at the forefront of disseminating and communicating scientific knowledge and technological innovation in the field to researchers, academics, entrepreneurs, companies, policy makers and the public worldwide.

Frontiers in Complex Systems covers fundamental questions, theories and general methodologies on complex systems as well as the cross-disciplinary application of these concepts and methods, often giving rise to new disciplines. It provides a forum for cross-disciplinary communication and welcomes quantitative research from different fields including Physics, Mathematics, Computer Sciences, Artificial Intelligence, Engineering, Climate change, Economics and Finance, Social Sciences, Linguistics, Ecology, Neuroscience, Health Sciences, Epidemics, Mobility and Transport, City Science, etc. Submissions to Frontiers in Complex Systems are made to appropriate specialty sections, each of which devoted to a specific sub-field and having their own expert editorial board. Aligned with the cross-disciplinary scope of the journal, some of these sections are shared with other Frontiers journals, providing an enhanced visibility of the research in different scientific communities.

More at: www.frontiersin.org

Complexity and Evolution

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

Entanglement, Symmetry Breaking and Collapse: Correspondences Between Quantum and Self-Organizing Dynamics

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

From autopoiesis to self-optimization: Toward an enactive model of biological regulation

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

Experiments with Social Network Interventions – Nicholas A. Christakis


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Network Science Society Colloquium – January 25, 2023

Nicholas A. Christakis
Experiments with Social Network Interventions

Abstract
Human beings choose their friends, and often their neighbors and co-workers, and we inherit our relatives; and each of the people to whom we are connected also does the same, such that, in the end, we assemble ourselves into face-to-face social networks that obey particular mathematical and sociological rules. Why do we do this? And how might a deep understanding of human social network structure and function be used to intervene in the world to make it better? Here, I will review recent research from our lab describing three classes of interventions involving both offline and online networks: (1) interventions that rewire the connections between people; (2) interventions that manipulate social contagion, modifying the flow of desirable or undesirable properties; and (3) interventions that manipulate the positions of people within network structures. I will illustrate what can be done using a variety of experiments in settings as diverse as fostering cooperation or the diffusion of innovation in networked groups online, to fostering health behavior change in developing world villages and towns. I will also discuss recent experiments with “hybrid systems” comprised of both humans and artificial intelligence (AI) agents interacting in small groups. Overall, by taking account of people’s structural embeddedness in social networks, and by understanding social influence, it is possible to intervene in social systems to enhance desirable population-level properties as diverse as health, wealth, cooperation, coordination, and learning.

About the Speaker
Nicholas A. Christakis, MD, PhD, MPH, is a social scientist and physician at Yale University who conducts research in the fields of network science, biosocial science, and behavior genetics. His current work focuses on how human biology and health affect, and are affected by, social interactions and social networks. He directs the Human Nature Lab and is the Co-Director of the Yale Institute for Network Science. He is the Sterling Professor of Social and Natural Science at Yale University, appointed in the Departments of Sociology; Medicine; Ecology and Evolutionary Biology; Biomedical Engineering; and the School of Management.

Watch at: www.youtube.com