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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
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Recent Additions: New and Updated Entries in the Past 60 Days
Displaying entries 1 through 15 of 102 found.

The Natural Genesis Vision

The Genesis Vision > Current Vistas

Georgiev, Georgi, et al, eds. Evolution, Development and Complexity: Multiscale Models of Complex Adaptive Systems. International: Springer, 2019. As the quote says, this is an eclectic collection from a satellite day at the main Cancun complexity conference, Google key words. Chapters include Universal Darwinism and the Origins of Order by John O. Campbell and Michael Price (search), Life, Intelligence and the Selection of Universes by Rudiger Vaas, A Multi-Scale View of the Emergent Complexity of Life by Casper Hesp, et al, Complexity, Development and Evolution in Morphogenetic Collective Systems by Hiroki Sayama and Applying Evolutionary Meta-Strategies to Human Problems by Valerie Gremillion.

This book explores the universe and its subsystems from the three lenses of evolutionary (contingent), developmental (predictable), and complex (adaptive) processes at all scales. It draws from the academic disciplines of complexity science, physical science, information and computer science, theoretical and evo-devo biology, cosmology, astrobiology, evolutionary theory, developmental theory, and philosophy. The chapters come from a Satellite Meeting, "Evolution, Development and Complexity" (EDC) hosted at the Conference on Complex Systems, in Cancun, 2017. This book explores many issues within the field of EDC such as the interaction of evolutionary stochasticity and developmental determinism in biological systems and what they might teach us about these twin processes in other complex systems.

The Evolution, Development and Complexity satellite meeting explores how our understanding of the universe as a complex system might be augmented by insights from information and computation studies, evolutionary developmental (evo-devo) processes applied at universal and subsystem scales. The Evo Devo Universe is an academic research and discussion community of international scholars investigating complex systems at all scales of universal dynamics. The satellite day seeks to evaluate complex adaptive systems at all scales of complexity science, physical science, information and computer science, theoretical and evo-devo biology, cosmology, astrobiology, evolution, development, and philosophy.

The Genesis Vision > Current Vistas

Hofkirchner, Wolfgang. A Paradigm Shift for the Great Bifurcation. Biosystems. June, 2020. The Institute for a Global Sustainable Information Society, Vienna philosopher (search) posts a current survey of his 21st century project to consider and facilitate a vital revolutionary advance from an olden machine model, now in ruins, to an organic, sustainable milieu graced by integrative, informed, systemic emergence.

This paper is an attempt to understand the global challenges that humanity is confronted with. It is argued that a secular paradigm shift is required away from a mechanistic picture of the world to accounts of emergence, of systemicity, informationality and conviviality, so as to provide a transdisciplinary science. Viewed by this perspective, current social evolution can be seen at a Great Bifurcation. Humankind is both on the brink of extinction, and the threshold of a planetary society. Another leap in integration would respond to the complex dilemma. Human beings as informational agents can establish convivial rules of living together on the way to a worldwide commons. By doing so, they would accomplish another evolutionary step in anthroposociogenesis. I will describe a Global Sustainable Information Society conceptual framework of necessary conditions for local and global conviviality. (Abstract excerpt)

The Genesis Vision > Current Vistas

Jeffery, Kate and Carlo Rovelli. Transitions in Brain Evolution: Space, Time and Entropy. Trends in Neuroscience. April, 2020. University College London and University of Aix-Marseille physicists offer a way that might reconcile these seemingly disparate features of our standard scientific model by observing that cerebral cognition can be seen to mitigate thermodynamic costs. Their endeavor is set within the major transitions scale whose nested increase of mobility and memory rises along with entropic expenditures. A concern then becomes our human, linguistic mode in its Anthropocene phase that is capable of this retrospective view. But the emergence course is not seen as physically guaranteed – it could have come to a dead end at some point. In closing, it is noted that this may still happen to we peoples if nuclear armaments and other terminal perils are not resolved.

How did brains evolve to become so complex, and what is their future? Brains pose an explanatory challenge because entropy, which inexorably increases over time, is commonly associated with disorder and simplicity. Recently we showed how evolution is an entropic process, building structures – organisms – which themselves facilitate entropy growth. Here we suggest that key transitional points in evolution extended organisms’ reach into space and time, opening channels into new regions of a complex multi-dimensional state space that also allows entropy to increase. Brain evolution enabled representation of space and time, which vastly enhances this process. (Abstract)

The Genesis Vision > Current Vistas

Richardson, Ken. In the Light of the Environment: Evolution through Biogrammars not Programmers. Biological Theory. June, 2020. The emeritus Open University, UK psychologist has for some time (search) felt that current efforts to form a revised, updated evolutionary synthesis continue to miss what moves and informs living organism systems. As this site avers and cites, an array of self-organizing agencies are at generative work prior to selective effects. For this reason, it is necessary to move beyond a genetic basis only, even if expansive. From our late vantage, it would seem that some manner of retained, knowledgeable content which is vital for survival in changing environments is what actually evolves, grows and emerges. For a name, this corpora quality is dubbed a “biogrammar.” We add four quotes about this insightful view.

Biological understanding of human cognitive functions is incomplete because of failure to understand the evolution of complex functions and organisms in general. Here, that failure is attributed to an aspect of the standard neo-Darwinian synthesis, namely commitment to evolution by natural selection of genetic programs in stable environments, a position that cannot easily explain the evolution of complexity. When we turn to consider more realistic, highly changeable environments, however, another possibility becomes clearer. An alternative to genetic programs—dubbed “biogrammars”—is proposed here to deal with complex, changing environments and explain evolving complexity from pre-genetic life to human socio-cognitive functions. (Abstract)

The purpose of this article is to show how these problems really stem from a failure to properly consider the complexity of environments of evolution, especially their changeability. Here it is suggested that what environmental changeability demands is not genetic programs, but inducible covariation grammars (“biogrammars”). By explaining evolving complexity, from primordial origins to human socio-cognition, it is suggested that biogrammars constitute the most interesting aspect of “what has evolved.” (1)

It is in such global patterns that cognition emerges as a distinct biogrammatical level. Sensory stimuli are highly variable and “noisy.” Yet our cognitive experience of the environment is much more stable and consistent. Order is created by ever-updating covariation patterns—cognitive biogrammars—rather than mere neural ones: a new level of
self-organized regulations, creating new levels of environmental predictability. (8)

Evolution by biogrammars explains key transitions to complexity on the basis of a single, unitary but powerful principle. It also puts into clearer context the role of natural selection. Darwin admitted that natural selection might not be the only path to evolution. Already, by 1904, De Vries and others were pointing out that nothing can be selected until it already exists. Self-organizing biogrammars, working with informational structure, create variation and novel adaptations far more rapidly and fruitfully than random genetic mutations and natural selection. (9)

The Genesis Vision > Current Vistas

Slijepcevic, Predrag. Natural Intelligence and Anthropic Reasoning. Biosemiotics. July, 2020. From our worldwide vantage, the Brunel University biophilosopher lays out a proposal that life’s Earthly evolution from bacterial to global cultures may well be appreciated as a relative increase in cognitive, information-gaining, semiotic intelligence. The oriented trajectory is seen to bolster an Anthropic Principle such that human persons have a cosmic agency so to bring quantified, descriptive knowledge into conscious awareness. Guidance along the way is provided by J. A. Wheeler’s participatory universe, Jesper Hoffmeyer’s semiotic scaffolding, and more. The notable surmise is once again of an encompassing reality made and meant for our late, vital act of informed observation and selective affirmation. See also Principles of Information Processing and Natural Learning in Biological Systems in Journal for General Philosophy of Science (October 2019) and Evolutionary Epistemology: A New Research Programme for Distributed Biological Intelligence in Biosystems (163/23, 2018) by the author.

This paper aims to justify the concept of natural intelligence in a biosemiotic context. I will argue that the process of life is a cognitive/semiotic process and that organisms, from bacteria to animals, are cognitive or semiotic agents. To justify this, the neural-type intelligence represented by the form of anthropic reasoning will be compared and with intelligences from four disciplines of biology – relational biology, evolutionary epistemology, biosemiotics and the systems view of life. The comparison will be done by asking questions related to observation and the notion of true observers. To answer the questions I will rely on a range of concepts including SETI (search for extraterrestrial intelligence), Fermi’s paradox, bacterial cognition, versions of the panspermia theory, as well as some new concepts including biocivilisations, cognitive/semiotic universes, and the multiverse. The key resolve is that the process of cognition/semiosis – the essence of natural intelligence – can be seen as a biological universal. (Abstract)

I define the Anthropic Principle as follows. The human-type intelligence (neural intelligence) and humanity-type civilization supported by techno-science, is the minimal type intelligence/civilisation capable of the true observation at the cosmic scale. I will also argue that there are no fundamental differences between the observing capacities of, for example, bacteria and Homo sapiens. Intelligence emerges not only in the case of interacting neural cells but also in the case of interacting bacteria that turn their colonies into brain-like entities. My argument is rooted in the notion that the process of life is inherently an observation-like process whereby all organisms are cognitive or semiotic agents and the process of evolution is a cognitive process, or semiotic scaffolding. (5)

In conclusion, natural intelligence may be viewed as a process equivalent to semiotic scaffolding, an important principle behind biosemiotics. Other disciplines, including relational biology, evolutionary epistemology and the systems view of life, interpret natural intelligence in a similar way to biosemiotics. Thus, the process of cognition/semiosis – the essence of natural intelligence – is a biological universal. The novelties explicated in this study include the concepts of true observers, biocivilisations and the cognitive/semiotic multiverse. (20)

Planetary Prodigy: A Sapiensphere Comes to Her/His Own Knowledge

A Learning Planet > Original Wisdom > The Book of Nature

Lample, Guillaume and Francois Charton. Deep Learning for Symbolic Mathematics. arXiv:1912.01412. We cite this entry by Facebook AI Research, Paris mathematicians here because at this frontier of computational studies, it refers to “Mathematics as a Natural Language.” The paper merited a news note Symbolic Mathematics Finally Yields to Neural Networks by Stephen Ornes in Quanta (May 20, 2020). While densely argued, the paper assumes a discernible legibility which resides deeply within natural creation. Some 400 years later, Galileo would be pleased.

Neural networks have a reputation for being better at solving statistical or approximate problems than at performing calculations or working with symbolic data. In this paper, we show that they can be surprisingly good at more elaborated tasks in mathematics, such as symbolic integration and solving differential equations. We propose a syntax for representing mathematical problems, and methods for generating large datasets that can be used to train sequence-to-sequence models. We achieve results that outperform commercial Computer Algebra Systems such as Matlab or Mathematica. (Abstract)

A Learning Planet > The Spiral of Science

Alexeev, Yuri, et al. Quantum Computer Systems for Scientific Discovery. arXiv:1812.07577. Twenty five select researchers from across the USA including John Preskill and Seth Lloyd (23 men and 1 woman Shelby Kimmel) report on a late 2019 meeting about how this analytic and computational frontier capability might be coordinated with megadata projects, studies and explorations from astrocosmic to social, climate and medical areas going forward. One might note that as such collaborative, planet scale projects advance (still sans asking whom and why, does a discovery await), human beings might well seem as the universe’s way of achieving its own consciously perceived self-description which it vitally needs to read, understand and select itself.

The great promise of quantum computers comes with the dual challenges of building them and finding useful applications. We argue that these aspects should be considered together by co-designing full-stack systems along with their intended use so to hasten development and potential for scientific discovery. In this context, we identify scientific and community needs, opportunities, case studies, and issues for the development of quantum computers for science. This document is written by a community of university, national laboratory, and industrial researchers in the field of Quantum Information Science and Technology, and is based on a NSF workshop on held in October 2019 in Alexandria, VA. (Abstract)

A Learning Planet > The Spiral of Science

Hardwicke, Tom, et al. Calibrating the Scientific Ecosystem through Meta-Research. Annual Review of Statistics. 7/11, 2020. As a big data tsunami engulfs quantum to genomic to astromic fields, Meta-Research Innovation Center Berlin and Stanford University scholars scope out ways to reorient and empower methods that can distill evidential patterns and findings. See also in this volume 21st Century Statistical and Computational Challenges in Astrophysics by Eric Feigelson, et al.

Modern astronomy has been rapidly increasing our ability to see deeper into the universe as it acquires enormous samples of cosmic populations. Gaining astrophysical insights from these datasets requires a wide range of sophisticated statistical and machine learning methods. Bayesian inference, central to linking astronomical data to nonlinear astrophysical models, addresses problems in solar physics, properties of star clusters, and exoplanet systems. The field of astrostatistics needs increased collaboration and joint development of new methodologies. Together, they will draw more astrophysical insights into astronomical populations and the cosmos itself.

While some scientists study insects, molecules, brains, or clouds, other scientists study science itself. Meta-research, or research-on-research, is an active discipline that investigates efficiency, quality, and bias in the scientific ecosystem, which is under some attack today. We introduce a translational framework that involves (a) identifying problems, (b) investigating problems, (c) developing solutions, and (d) evaluating solutions. In each of these areas, we review key meta-research endeavors and discuss examples of prior and ongoing work. (Abstract excerpt)

A Learning Planet > The Spiral of Science

Renn, Jurgen. The Evolution of Knowledge: Rethinking Science for the Anthropocene. Princeton: Princeton University Press, 2020. The MPI for the History of Science director publishes a collegial volume some 25 years in the making that from our late vantage achieves a fresh, integral surmise. Human history can now appear as a grand knowledge gaining project from Greece, China, and Europe to its present Anthropic worldwide transition. By such a vista, and in accord with this website, into the 21st century an epochal shift is much underway from individuals (men) and local groups to a “global learning process” (21) in the form of a collective, cumulative repository in its online noosphere (re V. Vernadsky and P. Teilhard). As we try to broach here, a new phase of guided facilitation so as to seek ways to better organize, translate and foster accessible usage. A detailed glossary with sections such as Cognitive Psychology and Science, Complex Systems Theory, Earth Systems, Epistemic Networks, and Knowledge Development then provides an expansive guide.

This book presents a new perspective about the history of science and technology, one that offers a grand narrative in which knowledge serves as a critical factor of cultural evolution. It examines the role of knowledge in global transformations going back to the dawn of civilization all the way to complex challenges confronting us today in the Anthropocene epoch shaped by humankind. Renn reframes the history of science and technology, analyzing key episodes such as the evolution of writing, the Scientific Revolution of early modernity, and the current digital globalization of scientific findings. (Publisher)

In chapter 13, we saw how epistemic communities may come into being by processes of self-organization involving cognitive networks. Clearly, even in its current form, the Web has immensely improved the conditions for such self-organizing networks. The challenges of the Anthropocene might act as a catalyst for the emergence of a global epistemic community beyond disciplinary trenches, for refocusing the Web on problems of knowledge, and for creating new bridges between the academic world and civil society. (408)

Epistemic Evolution: A process emerging from cultural evolution in which the knowledge economy of science has transformed from an accidental into a necessary condition for preserving, sharing, and developing the achievements of cultural evolution, and possibly even the survival of the human species on a global scale. (Glossary)

A Learning Planet > Mindkind Knowledge

Global Brain Institute. sites.google.com/site/gbialternative1.. The home page for this Free University of Brussels endeavor to engage and scope out into the 2010s the enveloping, vital presence of a worldwide cerebral faculty as it may gain an intelligence, knowledge and life of its own. The veteran director is Francis Heylighen, search for his comprehensive papers, and for members such as Clement Vidal, Marta Lenartowicz and Dirk Helbing.

We see people, machines and software systems as agents that communicate via complex network links. These agents contribute their own expertise to resolving problems and challenges. Thus the skills of different agents are pooled into a collective intelligence much greater than that of its individual members. This propagation across the global network is a complex process of self-organization. It is similar to the "spreading activation" that characterizes thinking in the human brain. This process will change the network by reinforcing useful links, while weakening less useful ones. So it can be said that the network learns and becomes more intelligent.

A Learning Planet > Mindkind Knowledge

Malone, Thomas. Superminds. Grand Haven, MI: Brilliance Publishing, 2019. The author is founding director of the MIT Center for Collective Intelligence. Along with this volume and You Tube presentations he does advise that this enveloping noosphere with its infinity of web linkages should be much smarter than nodal online users and ought achieve its own coherent knowledge. Indeed this may be the only way we can save ourselves. Into 2020, a good example could be the intense, global proliferation of COVID-19 data statistics, complex system analyses, and palliative proposals.

The MIT Center for Collective Intelligence explores how people and computers can be connected so that – collectively – they act more intelligently than any person, group, or computer has ever done before. (cci.mit.edu).

A Revolutionary Organic Habitable UniVerse

Animate Cosmos > Quantum Cosmology

Calcagni, Gianluca. Classical and Quantum Cosmology. Europe: Springer, 2017. A Spanish National Research Council physicist provides an 800+ page, 3,500 reference text compendium for this 21st century unification of infinitesimal quantum phenomena with an inflationary and temporally dynamic universe of infinite expanse. See also Quantum Cosmology by Martin Bojowald (Springer, 2011) for another integral volume.

This comprehensive textbook is devoted to classical and quantum cosmology, with an emphasis on quantum gravity and string theory and their observational imprint. It covers major challenges in theoretical physics such as the big bang and the cosmological constant. An extensive review of standard cosmology, the cosmic microwave background, inflation and dark energy sets the scene for the application of main quantum-gravity and string-theory models of cosmology.

Animate Cosmos > Quantum Cosmology

Hartle, James. Arrows of Time and Initial and Final Conditions in the Quantum Mechanics of Closed Systems Like the Universe. arXiv:2002.07093. We choose this recent entry by the UC Santa Barbara physicist to recognize his decadal flow of papers about the so mathematical matters of melding quantum depths with cosmic breadth. The third abstract is from a 1990 Jerusalem Winter School and well catches this human unification of depth and breadth. See also, for example, The Impact of Cosmology on Quantum Mechanics (1901.03933) and The Quantum Mechanics of Cosmology (1805.12246), abstracts below, for his oriented agenda.

In a quantum universe, arrows of time are described by the probabilities of appropriately coarse grained sets of histories of quantities like entropy that grow or decay. We show that the requirement of that these sets of histories decohere implies two things: (1) A time asymmetry between initial and final conditions that is a basis for arrows ot time. (2) How a final state of indifference that is represented by a final density matrix proportional to the unit density matrix is consistent with causality, and allows a finer-grained description of the model universe in terms of decoherent histories than any other final state. (Abstract, 2002.07093)

When quantum mechanics was developed in the '20s of the last century another revolution in physics was just starting. It began with the discovery that the universe is expanding. For a long time quantum mechanics and cosmology developed independently of one another. Yet the very discovery of the expansion would eventually draw the two subjects together because it implied the big bang where quantum mechanics was important for cosmology and for understanding our observations of the universe today. (Abstract, 1901.03933)

This posting is 92 pages of from the lectures by the author at the 7th Jerusalem Winter School 1990 on Quantum Cosmology and Baby Universes. The lectures covered quantum mechanics for closed systems like the universe, generalized quantum mechanics, time in quantum mechanics, the quantum mechanics spacetime, and practical quantum cosmology. (Abstract, 1805.12246).

Animate Cosmos > Quantum Cosmology > cosmos

Vazza, Franco. The Complexity and Information Content of Simulated Universes. arXiv:2007.05995. The University of Bologna astrophysicist (search) proposes a method to evaluate self-organized, scale-invariant spatial and temporal cosmic structures by way of their inherent informational qualities. A “morphology of complexity” is broached as a relative measure of stellar and galactic cluster formations. By a natural philoSophia view it is a wonder that 400 years after Galileo we collaborative peoples are able to explore and quantify such breadth and depth so as to “simulate” entire cosmoses. The innate occurrence of geometric regularities across a developmental course seems to imply, if of a mind to ask and see, the presence of a greater phenomenal reality for which our Earthling sapience has a central agency and import.

The emergence of a complex, large-scale organisation of cosmic matter into the Cosmic Web is a beautiful exemplification of how complexity can be produced by simple initial conditions and simple physical laws. In the epoch of Big Data in astrophysics, connecting the variety of multi-messenger observations to the complex interplay of fundamental processes is an open challenge. In this contribution, I discuss a few relevant applications of Information Theory to the task of measuring the complexity of numerical simulations of the Universe. When applied to cosmological simulations, complexity analysis allows us to monitor which physical processes are mostly responsible for the emergence of complex dynamical behaviour across cosmic epochs and environments. (Abstract excerpt)

Information Theory (IT) is a powerful and multidisciplinary field of investigation, which enables a mathematical representation of the conditions and parameters affecting the processing and the transmission of information across physical systems. According to IT, all physical systems - the entire Universe included - can be regarded as an information-processing device, which computes its evolution based on a software made of physical laws. Thanks to IT, the complexity of a process becomes a rigorous concept, which can be measured and compared, also between different fields of research. (2)

Animate Cosmos > Quantum Cosmology > quantum CS

Alon, Ofir and Axel Lode, eds. Quantum Many-Body Dynamics in Physics, Chemistry and Mathematics. Entropy. May, 2020. This is an introduction to a special collection issue by University of Haifa and Albert-Ludwig University, Freiburg physicists across this intersect of these quantum and classical fields and endeavors, which presently joining up again in common understanding.

The Schrödinger equation is central to quantum mechanics and a cornerstone for the description of many fascinating phenomena in AMO, chemical, condensed-matter, and nuclear physics. Quantum many-body dynamics attract an enormous amount of interest in physics, chemistry, and mathematics alike. The purpose of this Special Issue is to amalgamate contributions from researchers actively working on solutions, applications, and theoretical methodologies for the time-dependent Schrödinger equation for few- and many-particle systems. (Proposal)

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