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

Erdi, Peter. Complexity Defined. Berlin: Springer, 2007. A textbook due in June. As per the quote, insights into a new kind of genesis cosmos whose universal creative source instantiates at each emergent stage. But this epochal revolution and discovery has not yet registered, which is an aim of this website.

It is shown that very different complex phenomenon of nature and society can be analyzed and understood by nonlinear dynamics since many of the systems of very different fields, such as physics, chemistry, biology, economics, psychology and sociology, etc. have similar architecture. (Publisher’s website)

Feistel, Rainer and Werner Ebeling. Physics of Self-Organization and Evolution. Weinheim: Wiley-VCH, 2011. A thoroughly revised edition of a pioneer 1982 volume by the authors, who are German system scientists. At the center of European complexity thinking for over three decades, often in dialogue with Ilya Prigogine, Manfred Eigen, Herman Haken and many others, within the noted heritage of Gregor Hegel, the work is a substantial review of non-equilibrium thermodynamics, nonlinear dynamics, origins of life, evolutionary theories, and much more. A 2011 added emphasis is an appreciation of nature’s informational essence, which is seen to ascend with evolving generative structures and processes.

Fellermann, Harold, et al, eds. Artificial Life XII: Proceedings of the Twelfth International Conference on the Synthesis and Simulation of Living Systems. Cambridge: MIT Press, 2010. To everyone’s credit, the full text of this August 2010 meeting in Denmark was posted on the MIT Press site shortly afterwards. A sense of its cosmic scope can be gained by the seventeen sections listed below. Although many papers, Jerzy Maselko and Hiroki Sayama cited herein, may infer a greater organic genesis, with still no women among 27 organizers and section leaders, and few presenters, this imminent, vitalizing discovery, the very idea, yet awaits.

Chemical Self-Assembly and Complexity, Origin of Life, Bottom-up Synthetic Cells, Systems Biology, Biological and Chemical Information Processing and Production, Artificial Chemistries Minimal Cognition and Physical Intelligence, Evolutionary Dynamics, Theoretical and Computational Frameworks, Complex Networks, Ecology, Collective Intelligence, Emergent Engineering, Intelligence and Learning, Socio-Technical Systems, Philosophy.

Feudel, Ulrike, et al. Multistability and Tipping: From Mathematics and Physics to Climate and Brain: A Minireview. Chaos. 28/3, 2018. Physical chemists U. Feudel, University of Oldenburg, Alexander Pisarchik, Technical University of Madrid, and Kenneth Showalter, West Virginia University introduce an issue section for studies about these ubiquitous dynamic tendencies. They are distinguished by nonlinear attractor states and critical transitions which seem to instantiate in kind everywhere from quantum realms to stormy weather. Some papers herein are Emergence, Evolution, and Control of Multistability in a Hybrid Topological Quantum/Classical System; Detecting, Anticipating, Implications of Tristability in Pattern-Forming Ecosystems; and Predicting Critical Transitions in Spatially Extended Systems.

Multistability refers to the coexistence of different stable states in nonlinear dynamical systems. In this introduction, we introduce the classes of dynamical systems in which this phenomenon has been found and the concept of critical transitions. We then present some specific applications in physics, neuroscience, biology, ecology, and climate science. Many dynamical systems in nature possess several coexisting stable states (attractors) for a given set of parameters and/or external forcings — a phenomenon called multistability. Whenever such a coexistence of a multitude of states is found, the system can switch from one stable state to another either randomly by perturbations or in a desired way employing a control strategy or whenever parameters are varied in a specific way. These switchings are called critical transitions; in physics, they are also termed phase transitions. (Abstract edited excerpts)

Finlay, Bland, et al. Self-Similar Patterns of Nature. Proceedings of the Royal Society B. 273/1935, 2006. An extensive study from Britain and Denmark of insect diversities from meadow to bioregion reveals a constant nested series of size-frequency distributions across geometrical dimensions. So a grand new nature appears, it could be noted, no longer intractably tangled but comprehensible due to a universally repetitive archetype.

We have shown that the global diversity of insects is supported by a framework of self-similar patterns that emerge with some force, are relevant in Both Northern Southern Hemispheres, and across spatial scales from a few hectares to global. (1939) Finally, a further challenge will be to determine whether self-similar patterns lie hidden within other species-rich animal taxa. We suspect they do, and when they are revealed, they too will provide useful tools for characterizing and monitoring biodiversity across spatial scales. (1940)

Fitch, W. Tecumseh. Glossogeny and Phylogeny. Trends in Genetics. 24/8, 2008. Along with a rush of 2010 citations in A Cultural Code, one more realization that genomes and languages are an emergent manifestation of what might be seen as an independent, indeed parental, genome source.

Evolutionary theorists since Darwin have been interested in the parallels and interactions between biological and cultural evolution. Recent applications of empirical techniques originally developed to analyze molecular genetic data to linguistic data offer new insights into the historical evolution of language, revealing fascinating parallels between language change and biological evolution. This work offers considerable potential toward unified theories of genetic and cultural change. (373)

Flake, Gary. The Computational Beauty of Nature. Cambridge: MIT Press, 1998. A technical appreciation through nonlinear science of the recurrent harmony of the natural kingdoms. The website for the book with an extensive glossary is: www.mitpress.mit.edu/books/FLAOH/cbnhtml/home

….in order for the universe to move coherently from one state to the next, the universe must ‘remember’ previous states. (428) Looking at the organization of nature, we find that most interesting things are composed of smaller interesting things. Each level is nearly a universe in itself, since all of them use and support types of structural and functional self-similarity, multiplicity and parallelism, recursion and feedback, and self-reference. (429)

Fontana, Walter and Leo Buss. The Arrival of the Fittest. Bulletin of Mathematical Biology. 56/1, 1994. Its subtitle is “Toward a Theory of Biological Organization.” Since natural selection cannot explain how organisms occur in the first place, this oft-cited, important paper proposes that independent dynamic, autopoietic networks serve to organize a hierarchical scale of life.

Forrest, Stephanie and Melanie Mitchell. Adaptive Computation: The Multidisciplanary Legacy of John H. Holland. Communications of the ACM. August, 2016. University of New Mexico, and Portland State University complexity scientists write an insightful biography about this premier founder of the complexity revolution. Holland (1929-2015) was a pioneer professor of computer science at the University of Michigan, and is well known for his theory of genetic algorithms, which have gone on to many versions and applications. Holland also conceived the theory of complex adaptive systems (search JH) as a universal way to express such non-equilibrium evolutionary dynamics of statistical search and optimization.

Here, we consider this larger framework, sketching the recurring themes that were central to Holland’s theory of adaptive systems: discovery and dynamics in adaptive search; internal models and prediction; exploratory modeling; and universal properties of complex adaptive systems. (58) As the discussions about complex adaptive systems matured, a consensus developed about their basic properties. Such systems are composed of many components with nonlinear interactions; are characterized by complex emergent behavior; exhibit higher-order patterns; operate at multiple (and often nested) spatial and temporal scales, with some behavior conserved across all scales and other behaviors changing at different scales; and are adaptive, with behavioral rules continually adjusted through evolution and learning. (62)

Frame, Michael and Amelia Urry. Fractal Worlds: Grown, Built, and Imagined. New Haven: Yale University Press, 2016. A Yale mathematician and a journalist achieve a comprehensive, insightful survey of nature’s intrinsic self-similar topologies. To an integral degree not before covered, a nested self-similarity in kind is illuminated from galactic clusters, solar flares and planet formation to fitness landscapes, DNA globules, physiologies, broccoli florets, coastlines, clouds, onto literary narratives and human artifices. An Appendix lists 100 such instances, which are explained at length. Along with tutorials on how to calculate fractal dimensions, 50 reference pages make this a unique text. Michael Frame is most qualified for he was a junior colleague at Yale with Benoit Mandelbrot (1924-2010). Together they authored Fractals, Graphics, and Mathematics Education in 2002. MF with Nathan Cohn also wrote Benoit Mandelbrot: A Life in Many Dimensions, a 2014 biography. The volume is a grand survey from Mandelbrot’s 1970s and 1980s discovery to this witness of an invariant genesis from uniVerse to humanVerse.

Freeman, Walter. Foreword. Orsucci, Franco, ed. The Complex Matters of the Mind. Singapore: World Scientific, 1998. From the mid 1990s, a neuroscientist previews an imminent revolution in science.

Whereas the Newtonian dynamics that has dominated physics and biology for several centuries is rigid, deterministic, and precisely predictable, the new field of nonlinear dynamics opens a vast field of complexity to exploration and modeling. The key concept is self-organization. Given an adequate supply of energy and a sink for waste disposal, a collection of interacting elements such as molecules, neurons, organs or people can create new structure from within. (xiii)

Ganguly, Niloy, et al, eds. Dynamics On and Of Complex Networks: Applications to Biology, Computer Science, and the Social Sciences. Boston: Birkhauser, 2009. The proceedings of the Fourth European Conference on Complex Systems, Dresden, October 2007, with chapters by scientists from India and Germany. The meeting could well represent international collaborations entering upon a salutary genesis vista, out of the ruins of the 20th century. It is illuminating from the mid 2000s to see the project, as the quote notes, engage two distinct aspects – an initial distillation and discernment of independent, generic systems properties, and then their common, exemplary presence spreading to every area such as the book’s Biological, Social, and Informational Science sections.

The primary aim of this workshop was to systematically explore the statistical dynamics “on” and “of” complex networks that prevail across a large number of scientific disciplines. Dynamics on networks refers to the different types of processes, for instance, proliferation and diffusion, that take place on networks. The functionality/efficiency of these processes is strongly tied to the underlying topology as well as the dynamic behavior of the network. On the other hand, dynamics of networks mainly refers to the phenomena of self-organization, which in turn lead to the emergence of the complex structure of the network. Another important motivation of the workshop was to create a forum for researchers applying the theories of complex networks to various do mains as well as across several disciplines such as computer science, statistical physics, nonlinear dynamics, econometrics, biology, sociology and linguistics. (Preface)

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