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III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape4. Universal Evolution: A Celestial Expanse Fraix-Burnet, Didier, et al. The Phylogeny of Quasars and the Ontogeny of Their Central Black Holes. Frontiers in Astronomy and Space Science. February, 2017. A latest posting by the Institute of Planetology and Astrophysics of Grenoble natural philosopher about this project, here with Paola Marziani, Padova Astronomical Observatory, Mauro D’Onofrio, University of Padova, and Deborah Dultzin, UNAM Astronomical Institute, to sketch out an evolutionary astrocladistics (Google) for diverse galaxies akin to systematic groupings of organisms. See also their 2017 paper Phylogenetic Analyses of Quasars and Galaxies in this journal, along with Phylogenetic Tools in Astrophysics (1703.00286), The Phylogeny of Quasars (1702.02468), and Concepts of Phylogenetic Classification and Taxonomy (1606.016310 by Fraix-Burnet. For another perception see Cosmic Phylogeny by Paula Jofre, et al. A whole scale Cosmic Cladistics then seems a thought away so as to complete a universe to us developmental genesis. A latest posting by the Institute of Planetology and Astrophysics of Grenoble natural philosopher about this project, here with Paola Marziani, Padova Astronomical Observatory, Mauro D’Onofrio, University of Padova, and Deborah Dultzin, UNAM Astronomical Institute, to discern and construct an evolutionary astrocladistics (Google) for diverse galaxies akin to systematic groupings of organisms. See also their 2017 paper Phylogenetic Analyses of Quasars and Galaxies in this journal, along with Phylogenetic Tools in Astrophysics (1703.00286), The Phylogeny of Quasars (1702.02468), and Concepts of Phylogenetic Classification and Taxonomy (1606.016310 by Fraix-Burnet. For a further avail see Cosmic Phylogeny by Paula Jofre, et al. A whole scale Cosmic Cladistics then seems a thought away so as to complete a universe to us developmental genesis. Friston, Karl. The History of the Future of the Bayesian Brain. NeuroImage. 62/1230, 2012. After being immersed for two decades in British and American neuroscience, the now Scientific Director of the Wellcome Trust Center for Neuroimaging surveys the discovery in those years of a cerebral dynamic self-organization, along with a cognitive faculty distinguished by an interactive responsiveness via hierarchical scales in congruence with its greater environment. Such a “Bayesian brain” is busy with optimizing its “beliefs” about any input or reply, so as to minimize any expense of “free energy.” As Friston speaks for the field, the approach, via “statistical physics and information theory,” can be seen to reveal another means to join human and universe. Thomas Bayes (1701-1761) was a British mathematician and Presbyterian minister. Bayesian Statistics is a subset of the field of statistics in which the evidence about the true state of the world is expressed in terms of degrees of belief or, more specifically, Bayesian probabilities. Such an interpretation is only one of a number of interpretations of probability and there are many other statistical techniques that are not based on "degrees of belief". (Wikipedia) Goeree, Jacob, et al. Quantal Response Equilibrium: A Stochastic Theory of Games. Princeton: Princeton University Press, 2016. As the book summary notes, Goeree, a University of Technology Sydney physicist and economist, with Charles Holt, a University of Virginia political scientist, and Thomas Balfrey, a Caltech political economist, propose a more realistic theory to match actual individual and societal behaviors. Quantal Response Equilibrium presents a stochastic theory of games that unites probabilistic choice models developed in psychology and statistics with the Nash equilibrium approach of classical game theory. Nash equilibrium assumes precise and perfect decision making in games, but human behavior is inherently stochastic and people realize that the behavior of others is not perfectly predictable. In contrast, QRE models choice behavior as probabilistic and extends classical game theory into a more realistic and useful framework with broad applications for economics, political science, management, and other social sciences.
Grinin, Leonid, et al.
Evolutionary Megaparadigms: Potential, Problems, Perspectives.
Grinin, Leonid et al, eds.
Evolution: Cosmic, Biological, and Social.
Volgograd: Uchitel Publishing, 2011.
An introductory chapter for the first edition of an Almanac posted in full on the Sociostudies site (www.sociostudies.org) of its publisher. The editors and authors are Grinin, director of the Volgograd Center for Social Research, Andrey Lorotayev, Russian State University for the Humanities social anthropologist, Robert Carneiro, curator of the American Museum of Natural History, and Fred Spier, University of Amsterdam cosmic historian. But as The Russian Cosmists by George Young (Historic Prescience 2012) records, in contrast to Western analyses of an insensate, accidental reality, the traditional Russian mindset holds more to an Eastern, holistic persuasion. As a result, while cognizant of the latest science, an animate universe to human evolutionary genesis is allowed, akin to Vladimir Vernadsky, Pierre Teilhard de Chardin and a long heritage from Herbert Spencer to ancient Grecian origins. One of the clearest manifestations of the evolutionary approach is the form of universal evolutionism (Big History) that considers the process of evolution as a continuous and integral process – from the Big Bang all the way down to the current state of human affairs and beyond. Universal evolutionism implies that cosmic, chemical, geological, biological, and social types of macroevolution exhibit forms of structural continuity. The great importance of this approach (that has both the widest possible scope and a sound scientific basis) is evident. It strives to encompass within a single theoretical framework all the major phases of the universe, from the Big Bang down to forecasts for the entire foreseeable future, while showing that the present state of humankind is a result of the self-organization of matter. (10) Guglielmo, Magda, et al. A Genetic Approach to the History of the Magellanic Clouds. Monthly Notices of the Royal Astronomical Society. Online August, 2014. With Geraint Lewis and Joss Bland-Hawthorn, University of Sydney astrophysicists propose this novel procedure drawn from the field of bioinformatics to aid their studies of interstellar phenomena. As a result, a unique application of evolutionary biology terms, techniques, and selective processes to these far celestial reaches is achieved. The method is akin to the popular Bayesian statistics, also Markov processes, computational algorithms, which inference, altogether treat the cosmos as some manner of a universal Darwinism.
Harman, Willis and Elisabet Sathouris. Biology Revisioned. Berkeley, CA: North Atlantic, 1998. Noted elsewhere, for this section Sahtouris perceives a process of natural selection on a planetary and universe scale. My metaphor for the reproduction of cosmic life is that the Cosmos scatters planets as star seed, much as plants and animals here below scatter their seed. In both cases, only few seeds in this prolific venture of life actually “sprout” - those that land in the right conditions to support their continuing life. Jackson, Holly, et al. Using Heritability of Stellar Chemistry to Reveal the History of the Milky Way. arXiv:2011.06453. For a paper to appear in the Monthly Notices of the Royal Astronomical Society, an international, interdisciplinary team from MIT, University of Diego Portales, Chile (Paula Jofre, search), Cambridge University, and the University of Surrey (Robert Foley) continue to perceive and advance evident comparisons between biological and astrophysical evolutionary patterns and processes. Since chemical abundances are inherited between generations of stars, we use them to trace the evolutionary history of our Galaxy. We present a robust methodology for creating a phylogenetic tree, a biological tool often used to study heritability. Combining our phylogeny with information on stellar ages and dynamical properties, we reconstruct the shared history of 78 stars in the solar neighborhood. The branching pattern in our tree supports a scenario in which the thick disk is an ancestral population of the thin disk. In this paper, we demonstrate how a biological, phylogenetic perspective can help study key processes that have contributed to the evolution of the Milky Way. (Abstract excerpt) Jofre, Paula, et al. Cosmic Phylogeny: Reconstructing the Chemical History of the Solar Neighborhood with an Evolutionary Tree. Monthly Notices of the Royal Astronomical Society. 467/1, 2017. Paula Jofre, a Cambridge University astronomer, with Universidad Diego Portales, Chile, astronomer Payel Das, Universitat Pompeu Fabra, Spain, biologist Jaume Bertranpetit, and Cambridge University anthropologist Robert Foley contribute to a novel reconsideration of stellar and galactic dynamics by way of branching populations of organisms. With a recognition of prior work by Didier Fraix-Burnet (search) and others, phylogenetic trees are constructed for stars in the Milky Way, dubbed an astrocladistics, so as to extend Darwinian evolution across the celestial raiment. See also Galactic Phylogenetics by Paula Jofre and Payel Das at arXiv:1709.09338. Using 17 chemical elements as a proxy for stellar DNA, we present a full phylogenetic study of stars in the solar neighbourhood. This entails applying a clustering technique that is widely used in molecular biology to construct an evolutionary tree from which three branches emerge. These are interpreted as stellar populations that separate in age and kinematics and can be thus attributed to the thin disc, the thick disc and an intermediate population of probable distinct origin. Combining the ages of the stars with their position on the tree, we are able to quantify the mean rate of chemical enrichment of each of the populations, and thus show in a purely empirical way that the star formation rate in the thick disc is much higher than that in the thin disc. Our method offers an alternative approach to chemical tagging methods with the advantage of visualizing the behaviour of chemical elements in evolutionary trees. (Abstract) Joosten, Joost. Complexity Fits the Fittest. Zelinka, Ivan, et al, eds. How Nature Works: Complexity in Interdisciplinary Research and Applications. Berlin: Springer, 2014. The University of Barcelona logician is affiliated with the Algorthmic Nature group of the Paris-based Laboratory for Scientific Research for the Natural and Digital Sciences. By a general application of Stephen Wolfram’s cellular automata, the real presence a generative computational source in effect prior to selection can now be theoretically explained. This chapter, and a companion paper “On the Necessity of Complexity,” are available on the arXiv website. In this paper we shall relate computational complexity to the principle of natural selection. We shall do this by giving a philosophical account of complexity versus universality. It seems sustainable to equate universal systems to complex systems or at least to potentially complex systems. Post’s problem on the existence of (natural) intermediate degrees then finds its analog in the Principle of Computational Equivalence (PCE). In this paper we address possible driving forces—if any—behind PCE. Both the natural aspects as well as the cognitive ones are investigated. We postulate a principle GNS that we call the Generalized Natural Selection principle that together with the Church-Turing thesis is seen to be in close correspondence to a weak version of PCE. Next, we view our cognitive toolkit in an evolutionary light and postulate a principle in analogy with Fodor’s language principle. (Complexity Fits the Fittest) Knott, Paul. Decoherence, Quantum Darwinism, and the Generic Emergence of Our Objective Classical Reality. arXiv:1811.09062. A University of Nottingham, Center for the Theoretical Physics of Quantum Non-Equilibrium Systems mathematician continues to make better sense of this theoretical frontier as it becomes more amenable and familiar. Visit the author’s website at knottquantum.weebly.com for publications, a blog and an illustrated book Our Quantum Reality with engaging entries to many concepts. An earlier version of his work with colleagues is Generic Emergence of Objectivity of Observables in Infinite Dimensions in Physical Review Letters (121/160401, 2018). Also check the UN Center for QS site for examples of how this arcane phase is lately seen to have multifractal, informative, gravity, algorithmic (1812.01032) qualities. A University of Nottingham, Center for the Theoretical Physics of Quantum Non-Equilibrium Systems mathematician continues to make better sense of this theoretical frontier as it becomes more amenable and familiar. Visit the author’s website at knottquantum.weebly.com for publications, a blog and an illustrated book Our Quantum Reality with engaging entries to many concepts. An earlier version of his work with colleagues is Generic Emergence of Objectivity of Observables in Infinite Dimensions in Physical Review Letters (121/160401, 2018). Also check the UN Center for QS site for examples of how this arcane phase is lately seen to have multifractal, informative, gravity, algorithmic (1812.01032) qualities. Knuth, Kevin. Information-Based Physics: An Observer-Centric Foundation. Contemporary Physics. Online January, 2014. The SUNY Albany professor of physics and informatics continues the inspiration of John Archibald Wheeler that this exisstent reality is in some way founded upon and most distinguished by a communicative source and conveyance. Such a self-visualizing and activating cosmos then requires at a later point the presence of sentient observers to recognize, acknowledge, and so bring into full being. Knuth has a series of prior papers on arXiv such as The Physics of Events: A Potential Foundation for Emergent Space-Time. While they, and most theoretical papers, are written in a technical parlance, the point of the message could be that human beings are in fact significantly empowered and entitled to learn, discover, witness and self-select. It is generally believed that physical laws, reflecting an inherent order in the universe, are ordained by nature. However, in modern physics the observer plays a central role raising questions about how an observer-centric physics can result in laws apparently worthy of a universal nature-centric physics. Over the last decade, we have found that the consistent apt quantification of algebraic and order-theoretic structures results in calculi that possess constraint equations taking the form of what are often considered to be physical laws. The result is an approach to foundational physics where laws derive from both consistent descriptions and optimal information-based inferences made by embedded observers. (Abstract excerpt) Kording, Konrad. Bayesian Statistics: Relevant for the Brain? Current Opinion in Neurobiology. 25/130, 2014. In a special issue on Theoretical and Computational Neuroscience, a Northwestern University biophysicist advocates this approach which is lately coming into use across the sciences for optimal choices from a population of options. A best or sufficient bet is achieved by according new experience and/or responses with prior learned memory. For example, Richard Watson, et al (search 2014) proposes life’s evolution as proceeding this way. See also Automatic Discovery of Cell Types and Microcircuitry from Neural Connectomics by Kording and Eric Jonas at arXiv:1407.4137. The whole issue of some 32 articles, e.g. by Adrienne Fairhall, Stanislav Dehaene, and Leslie Valiant, is a significant entry to an endeavor by worldwise humanity to reveal the creaturely cerebration that brought me and We to be. With “connectome” often cited, the papers seem as if they could equally apply to genomes. Might a better term be a “neurome” equivalent? Bayesian statistics can be seen as a model of the way we understand things. Our sensors are noisy and ambiguous as several worlds could give rise to the same sensor readings. We therefore have uncertainty in our data and cannot be certain which model or hypothesis we should believe in. However, we can considerably reduce uncertainty about the world using previously acquired knowledge and by interpreting data across sensors and time. As new data comes in, we update our hypotheses. Bayesian statistics is the rigorous way of calculating the probability of a given hypothesis in the presence of such kinds of uncertainty. With Bayesian statistics, previously acquired knowledge is called prior, while newly acquired sensory information is called likelihood. (130)
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