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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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IV. Ecosmomics: An Independent, UniVersal, Source Code-Script of Generative Complex Network Systems

Hazen, Robert. Emergence and the Origin of Life. Astrobiology. 1/3, 2001. An abstract from the NASA Astrobiology Institute General Meeting, April 2001. The study of life and intelligence on the scale of the universe gives credence to its self-organizing dynamics and their resultant planes of sentient complexity.

The geochemical origin of life may be modeled as a sequence of ‘emergent’ events, each of which adds to molecular complexity and order….Natural systems with many interacting components, such as atoms, molecules, cells or stars, often display complex, ‘emergent’ behavior not associated with their individual components….This observed emergent behavior of highly ordered systems, including galaxies, planets, and life, points to a universal organizing principle. (301)

Helbing, Dirk. Traffic and Related Self-driven Many-particle Systems. Reviews of Modern Physics. 73/4, 2001. A technical survey of how human behavioral patterns such as vehicular and pedestrian traffic have a mathematical basis in terms of nonlinear dynamical theories. This power-law criticality is then seen to similarly apply to biological, economic, and cognitive systems.

Heylighen, Francis, et al, eds. The Evolution of Complexity. Dordrecht: Kluwer Academic, 1999. One of eight volumes from the interdisciplinary Einstein Meets Magritte conference held in Brussels in 1996. Each book is a color of the rainbow plus white. An abstract from the “Violet” book summarizes its theme:

The basic idea is that evolution leads to the spontaneous emergence of systems of higher and higher complexity or ‘intelligence’ from elementary particles, via atoms, molecules, living cells, multicellular organisms, plants and animals to human beings, culture and society. The volume thus wishes to revive the trans-disciplinary tradition of general systems theory by integrating the recently developed insights of the ‘complex adaptive systems’ approach, pioneered among others by the Santa Fe Institute. (xiii)

Holland, John. Emergence. Reading, MA: Addison-Wesley, 1998. Further explorations by the University of Michigan systems theorist with an emphasis on nature's tendency to deploy ascendant scales of complexity.

We are everywhere confronted with emergence in complex adaptive systems - ant colonies, networks of neurons, the immune system, the Internet, and the global economy, to name a few - where the behavior of the whole is much more complex than the behavior of the parts. There are deep questions about the human condition that depend on understanding the emergent properties of such systems. (2)

Holland, John. Hidden Order. Reading, MA: Addison-Wesley, 1995. An introduction to complex adaptive systems by one of its founders. In the author’s technical terms, many autonomous agents engaged in networks of interaction, immersed in an environment, and guided by tacit rules, will give rise to emergent organization and behavior.

Holovatch, Yurij, et al. Complex Systems: Physics beyond Physics. European Journal of Physics. 38/023002, 2017. (arXiv:1610.01002) Physicists Holovatch, National Academy of Sciences of Ukraine, Ralph Kenna, Coventry University, and Stefan Thurner, Medical University of Vienna, report on how much nonlinear complexity phenomena seems in effect across every social, urban, cultural and economic domain.

Complex systems are characterized by specific time-dependent interactions among their many constituents. As a consequence they often manifest rich, non-trivial and unexpected behavior. Examples arise both in the physical and non-physical world. The study of complex systems forms a new interdisciplinary research area that cuts across physics, biology, ecology, economics, sociology, and the humanities. In this paper we review the essence of complex systems from a physicist's point of view, and try to clarify what makes them conceptually different from systems that are traditionally studied in physics. Our goal is to demonstrate how the dynamics of such systems may be conceptualized in quantitative and predictive terms by extending notions from statistical physics and how they can often be captured in a framework of co-evolving multiplex network structures. We mention three areas of complex-systems science that are currently studied extensively, the science of cities, dynamics of societies, and the representation of texts as evolutionary objects. (Abstract)

Hooker, Cliff, ed. Philosophy of Complex Systems. Amsterdam: Elsevier, 2011. Volume 10 in Elsevier’s Handbook of the Philosophy of Science series. As the table of contents excerpt attests, the 1,000 page tome is a significant recognition of nature’s nonlinear creative energies across the span of material, evolutionary, genomic, biological, cognitive, ecological, social, economic, and artifactual domains. Salient chapters by Moreno, et al, Newman, Snyder, et al, Gao and Herfel, Rickles, are reviewed separately. But the corpus, by 34 men and 3 women, remains by habit unable to realize that not only a novel theoretical approach is found, a profound spontaneous, iterative emergence from cosmos to child is being discovered. We should note, for further example, Adam Sheya and Linda B. Smith’s chapter Dynamics of the Process of Development whence the same fluid patterns that grace galaxies are at work in our early years. And several papers, it ought to be noted, allude in closing that if such an insightful natural knowledge is gained, we are invited to imagine a new future “synthetic” creation.

Part I. General Foundations Introduction to Philosophy of Complex Systems. (Cliff Hooker), Systems and Process Metaphysics (Mark H. Bickhard), Computing and Complexity: Networks, Nature and Virtual Worlds (David G. Green and Tania Leishman), Evolutionary Games and the Modelling of Complex Systems (William Harms) General System Theory (Wolfgang Hofkirchner and Matthias Schafranek),
Conceptualising Reduction, Emergence and Self-organisation in Complex Dynamical Systems (Cliff Hooker).

Part II. Biology Complex Biological Mechanisms: Cyclic, Oscillatory, and Autonomous (William Bechtel and Adele Abrahamsen), The Impact of the Paradigm of Complexity on the Foundational Frameworks of Biology and Cognitive Science (Alvaro Moreno, Kepa Ruiz-Mirazo, and Xabier Barandiaran), Complexity in Organismal Evolution (Stuart A. Newman), Part III. Ecology Constructing Post-classical Ecosystems Ecology: The Emerging Dynamic Perspective from Self-organising Complex Adaptive Systems (Yin Gao and William Herfel), Complex Ecological Systems (Jay Odenbaugh)

Part V. Climatology The Complex Dynamics of the Climate System: Constraints on our Knowledge, Policy Implications and the Necessity of Systems Thinking (Carolyn W. Snyder, Michael D. Mastrandrea, and Stephen H. Schneider). Part VII. Anthropology Complexity and Anthropology (J. Stephen Lansing and Sean S. Downey). Part VIII. Psychology Dynamics of the Process of Development (Adam Sheya and Linda B. Smith), Living in the Pink: Intentionality, Wellbeing, and Complexity (Guy C. Van Orden, Heidi Kloos and Sebastian Wallot.

Ilachinski, Andrew. Cellular Automata. Singapore: World Scientific, 2001. A treatise on the computer based physics and mathematics of nonlinear systems. By this approach, a discrete, information-rich universe is revealed in a process of organizing and discovering itself by way of the same generative dynamics everywhere. Theoretical support is then achieved for a radically creative, increasingly personified reality. Ilachinski, a Russian-American systems scientist, comes to a quite different reading by way of these theories than does Stephen Wolfram.

Cellular automata (CA) are fundamentally the simplest mathematical representations of a much broader class of complex systems (where, for the moment, ‘complex system’ means any dynamical system that consists of more than a few - typically nonlinearly - interacting parts). As such, CA have proven to be extremely useful idealization of the dynamical behavior of many real complex systems…. (1)

Do the complex machinations of the world commodities market, the intricate swirls of the Belousov-Zhabotinski chemical reaction, the firings of the neurons in my brain and the interconnected co-evolving patterns of the earth’s global ecosystem all obey the same core set of underlying universal principles? While no-one yet knows the “deep” answer, evidence strongly suggests that the qualitative behavior of systems that emerge on the macro-scale is often very similar for systems that share the same basic structural organization, the same basic set of interactions among the components out of which they are constructed, the same basic patterns of information flow, etc. (612)

Jasny, 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. 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)

We discuss a simple model of co-evolution. In order to emphasize the effect of interactions between individuals, the entire population is subjected to the same physical environment. Species are emergent structures and extinction, origination and diversity are entirely a consequence of co-evolutionary interaction between individuals. For comparison, we consider both asexual and sexually reproducing populations. In either case, the system evolves through periods of hectic reorganization separated by periods of coherent stable coexistence. (2002 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)

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