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IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script SourceJasny, Barbara, et al. Connections. Science. 325/405, 2009. An introduction to a special update section on the state of “Complex Systems and Networks” theory. Papers include a review of “socioeconomic physics,” nature’s “tangled bank” mathematically revealed, technological dynamics, and a 10 year retrospective by Albert-Laszlo Barabisi how scale-free networks are now being found everywhere. For decades, we tacitly assumed that the components of such complex systems as the cell, the society, or the internet are randomly wired together. In the past decade, an avalanche of research has shown that many real networks, independent of their age, function, and scope, converge to similar architectures, a universality that allowed researchers from different disciplines to embrace network theory as a common paradigm. (Barabasi, 412) Jensen, Henrik. Complexity Science: The Study of Emergence. Cambridge. UK: Cambridge University Press, 2023.. Cambridge. UK: Cambridge University Press, 2023. The Imperial College London mathematician (search) writes a latest comprehensive textbook for this nascent 21st century study of our actual lively, anatomic, physiological, procreativity. Its contents course from first theoretic principles to statistical mechanics, networks, information, much more and onto critical transitions and tipping points. Jensen, Henrik. Tangled Nature: A Model of Emergent Structure and Temporal Mode Among Co-Evolving Agents. arXiv:1807.04228. In an invited contribution for a European Journal of Physics Focus on Complexity section, the Imperial College London biomathematician reviews this effective approach. Its initial posting was Tangled Nature: A Model of Evolutionary Ecology in the Journal of Theoretical Biology (216/73, 2002) by Jensen and colleagues, with many papers in between, as cited in its long bibliography. The technical concept is explained, along with recent integrations with complexity and network phenomena. Its wider employ across bacteria, food webs, migrations, species populations, onto to economies, sustainability and Gaian earth systems then follows. See also Tangled Worldview Model of Opinion Dynamics by Jensen's group at 1901.06372. Understanding systems level behaviour of many interacting agents is challenging in various ways, here we'll focus on the how the interaction between components can lead to hierarchical structures with different types of dynamics, causations or levels. We use the Tangled Nature model to discuss the co-evolutionary aspects connecting the microscopic individual to the macroscopic systems level. At the microscopic level the individual agent may undergo evolutionary changes due to mutations of strategies. The micro-dynamics always run at a constant rate. Nevertheless, the system's level dynamics exhibit an intermittent abrupt dynamics where major upheavals keep throwing the system between meta-stable configurations. We discuss the ecological and macroevolutionary consequences of the adaptive dynamics and briefly describe work using the Tangled Nature framework to analyse problems in economics, sociology, innovation and sustainability. (2018 Abstract) Johnson, Stephen. Emergence. New York: Scribner, 2001. A computer scientist and writer explains how a spontaneously creative nature employs the same pattern and dynamics of multiple interacting agents at every stage from social insects to neural nets, cities, and computer software. Kashtan, Padav and Uri Alon. Spontaneous Evolution of Modularity and Network Motifs. Proceedings of the National Academy of Sciences. 102/13773, 2005. Another example of how new understandings of evolution by way of complexity theory can identify a universally emergent structure and dynamics. Biological networks have an inherent simplicity: they are modular with a design that can be separated into units that perform almost independently. Furthermore, they show reuse of recurring patterns termed network motifs. (13773) Kauffman, Stuart. Investigations. New York: Oxford University Press, 2000. More conceptual insights into a view of Earth life that creates itself by means of intentional, autonomous agents which continually expand the niche of animate complexity. Kauffman’s frontier thinking offers glimpses of a “fourth law of thermodynamics,” a “general biology” for emergent life, autocatalytic biospheres, and a “coconstructing cosmos.” Kauffman, Stuart. The Origins of Order: Self-Organization and Selection on Evolution. New York: Oxford University Press, 1993. A breakthrough work that reports on biologist and physician Kauffman’s decades of research studies on a deep theoretical basis for the innate self-organization of complex living systems which is in creative effect prior to the winnowing action of natural selection. (Also see Kauffman’s At Home in the Universe in Part III,An Organic Universe.) Kelso, Scott and David Engstrom. The Complementary Nature. Cambridge: MIT Press, 2006. This important work is mainly noted in Current Vistas and by an extensive review in Recent Writings. Khelifi, Mounir, et al. A Relative Multifractal Analysis. Chaos, Solitons and Fractals. Vol. 140, 2020. University of Monastir, Tunisia mathematicians provide a further finesse of nature’s infinite self-similar formulations. We also cite amongst a wide array of international 2020 papers such as Multifractal Analysis of Embryonic Eye Structures in Mice (Sijilmassi, Ouafa, et al, Universidad Complutense de Madrid, 138), The Origin of Collective Phenomena in Firm Sizes (Ji, Guseon, et al, Graduate School of Future Strategy, KAIST, S. Korea, 136), Using Network Science to Unveil Badminton Performance Patterns (Gomez, Miguel-Angel, et al, Universidad Politécnica de Madrid, 135), A Symbiosis between Cellular Automata and Genetic Algorithms (Cerruti, Umberto, et al, University of Torino, 134), and The Fractal Description Model of Rock Fracture Networks (LiLi, Sui, et al, North China Institute of Science, 129). Our aim is to document in this consummate year how every manifest social, biologic and physical phase is deeply guided by common mathematic sources. The University of Monastir is a Tunisian multidisciplinary university with its own financial and administrative autonomy located on the Gulf of Hammamet, south of Tunis. It was founded in 2004 following the reform of the university higher education system and is organized in 5 Faculties, 2 graduate schools and 9 institutes. Kiel, L. Douglas. Knowledge Management, Organizational Intelligence and Learning, and Complexity. UNESCO-EOLSS Joint Committee. Knowledge for Sustainable Development. Volume 1. Paris: UNESCO Publishing; Oxford: EOLSS Publishers, 2002. A good primer on complexity sciences. As these become more familiar, they are motivating organizations to become dynamic, adaptive, ecologically sensitive and constantly learning. These discoveries focus on both order and disorder in the universe and on the increasing complexity and similarities across universal process, and have led to a new paradigm in the sciences – the self-organizing paradigm that focuses on how form and structure are produced in a dynamic and creative universe. (854) There is a growing recognition that the same processes that lead to a self-organizing universe have also led to the tremendous complexity of human cultures and human affairs. (855)
Krakauer, David, ed.
Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute 1984 – 2019.
Santa Fe, NM: Santa Fe Institute Press,
2019.
The SFI evolutionary biologist and current president gathers 35 years of contributions from events, seminars, projects, talks, and more which can well track the revolutionary discovery of a natural anatomy, physiology, cerebral, and cultural essence. A 1984 - 1999 section notes Mavericks such as John Holland, Murray Gell-Mann, and Simon Levin. 2000 - 2014 turns to Unifers like Harold Morowitz, Jessica Flack and Brian Arthur. 2015 and Beyond then completes 37 chapters with entries by Luis Bettencourt, Geoffrey West, Mirta Galesic, Simon DeDeo, Samuel Bowles, and Jennifer Dunne. Ultimately, we can argue that it is the self-similarity of the structure of fundamental physical law that dictates the continuing usefulness of mathematics. At the modest level of earlier science, this sort of self-similarity is strikingly apparent. Electricity, gravitation, and magnetism all have the same force, and Newton suggested that there might be some short-range force. Now that scientists are paying attention to scaling phenomena, we see in the study of complex systems astonishing power laws extending over many orders of magnitude. The renormalization group turns out to apply not only to condensed matter but to numerous other subjects. The biological and social sciences are just as much involved in these discoveries of scaling behavior as the physical sciences. We are always dealing with nature consonant and conformable to herself. So the approximate self-similarity of the laws of nature runs the gamut from underlying laws of physics to the phenomenological laws of the most complex realms. (Murray Gell-Mann, 1992, 38-39) Krishnagopal, Sanjukta, et al. Synchronization Patterns: From Network Motifs to Hierarchical Networks. arXiv:1607.08798. In this prepost of a paper to appear in Philosophical Transactions A, Technical University of Berlin physicists including Eckehard Scholl try to define these common characteristics of a universally nonlinear nature. Of special note is a choice of brain neural networks as a prime exemplar, as if a cerebral microcosm for all complex, self-organizing systems. In regard, as their presence becomes evident from quantum to cultural realms, an analogous macrocosm may once again well accord with human qualities We investigate complex synchronization patterns such as cluster synchronization and partial amplitude death in networks of coupled Stuart-Landau oscillators with fractal connectivities. The study of fractal or self-similar topology is motivated by the network of neurons in the brain. This fractal property is well represented in hierarchical networks, for which we present three different models. In addition, we introduce an analytical eigensolution method and provide a comprehensive picture of the interplay of network topology and the corresponding network dynamics, thus allowing us to predict the dynamics of arbitrarily large hierarchical networks simply by analyzing small network motifs. We also show that oscillation death can be induced in these networks, even if the coupling is symmetric, contrary to previous understanding of oscillation death. Our results show that there is a direct correlation between topology and dynamics: Hierarchical networks exhibit the corresponding hierarchical dynamics. This helps bridging the gap between mesoscale motifs and macroscopic networks. (Abstract)
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