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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
Recent Additions

I. Our Personphere Edition: A 21st Century, Planatural philoSophia, eLibrary of eCosmos Resource

C. Earthropo Sapience: A 2020s Convergent, Common, One Code, UniVerse to PediaVerse Genesis Synthesis

Teuscher, Christof. Revisiting the Edge of Chaos: Again?.. Biosystems. May, 2022. The veteran Portland State University systems theorist looks back over the course of this perception all the way to Stuart Kauffman’s autocatalysis whereof life prefers to seek and reside at an active poise between more or less order. Albeit along the way there were doubts, problems and variations, but it can indeed once more be affirmed that this optimum balance does seem to be in prevalent effect across much natural and social phenomena. Which into 2022, with L. da Costa and myriad other confirmations, would constitute an epochal, salutary discovery.

Does biological computation happen at some sort of “edge of chaos”, a dynamical regime somewhere between order and chaos? And if so, is this a fundamental principle that underlies self-organization, evolution, and complex natural and artificial systems that are subjected to adaptation? In this article, we will review the literature on the fundamental principles of computation in natural and artificial systems at the “edge of chaos”. The term was coined by Norman Packard in the late 1980s. Since then, the concept of “adaptation to the edge of chaos” was demonstrated and investigated in many fields where both simple and complex systems receive some sort of feedback. Besides reviewing both historic and recent literature, we will also review critical voices of the concept. (Excerpt)

Tononi, Giulio, et al.. Only What Exists can Cause: An Intrinsic View of Free Will. arXiv:2206.02069. premier team of GT, Larissa Albantakis, Chiara Cirelli, and Melanie Boly, University of Wisconsin, along with Christof Koch, Allen Institute for Brain Science continue to advance this Integrated Information Theory view as it gains a popular validity. In regard, a table of Axioms: the essential properties of phenomenal existence by way of Intrinsicality, Composition, Information, and Exclusion is entered. A table of Postulates: physical existence then shows how the same qualities can be traced to a deep natural basis. As this section reports, since circa 2008 these developments seem to well define a parallel ascent of informed complexity and knowing consciousness.

This essay addresses the implications of integrated information theory (IIT) for free will. IIT is about what consciousness is and how it occurs. According to IIT, the presence of aware sentience is accounted for by a maximum of cause-effect power in the brain. Thus the way specific experiences feel is due to how that cause-effect power is structured. If IIT is right, we do have free will in the fundamental sense: we have real alternatives, we make decisions, and we - not our neurons or atoms - are the cause of willed actions responsibilities. IIT's claim of true free will is based on the proper understanding of consciousness drawn from its intrinsic powers ontology: what truly exists, in physical terms, are intrinsic entities. (Abstract)

Udrescu, Silviu-Marian, et al. AI Feynman 2.0: Pareto Optimal Symbolic Regression Exploiting Graph Modularity. arXiv:2006,10762. MIT and Stanford physicists including Max Tegmark conceive and employ further effective techniques that can inform and serve this global computational ascent.

We present an improved method for symbolic regression that seeks to fit data to formulas that are Pareto-optimal and have the best accuracy for a given complexity. We develop a method for discovering generalized symmetries (arbitrary modularity in the computational graph of a formula) from gradient properties of a neural network fit. We use normalizing flows to generalize and aid probability distributions for which we only have samples, along with statistical hypothesis testing. (Excerpt)

Wuppuluri, Shyam and Ian Stewart, eds. Electrons to Elephants to Elections. International: Springer Frontiers, 2022. An Indian editorial philosopher and and the British mathematician and author here gather and arrange some 45 chapters so as to illustrate and flesh out that from our late vantage nature’s evident course from universe to human can be as some manner of emergence. This broad theme unites essays from physical and biological to personal and social phases. whereby we need take leave of a bottomed-out reduction method. The entries variously agree on a scalar, recurrent hierarchy which frames an oriented ascent from quantum realms through life’s long, sentient evolution onto cultural behaviors. By this view, some manner of self-similar recurrence in sequential kind can be perceived. A paper which richly evinced was Shared Mathematical Content in the Context of Complex Systems by the Jacobs University physicist Hildegard Meyer-Ortmanns (search), whose Abstract is next. Overall, these intellectual endeavors do seem closer to an encoded natural genesis of complexity, awareness and persons.

We pursue reduction to mathematics rather than materiality which seems more likely to underlie universal phenomena in different contexts. We illustrate with examples of increasing complexity. Firstly, by way of a set of differential equations which apply to pattern formation in biology and to classical mechanics. We then refer to the asymptotics of singular behavior at criticality between various substances. Thirdly, a set of stochastic reactions gives rise to emergent ecological phenomena which corresponds to a transition from species coexistence to extinction.. The fourth case is about Tracy-Widom probability distributions which observes universality classes in wide occurrence. (H. Meyer-Ortmanns excerpt)

Zanin, Massimiliano and Johann Martinez. Analysing International Events through the Lens of Statistical Physics: The Case of Ukraine. arXiv:2203.07403. IFISC Institute for Cross-Disciplinary Physics and Complex Systems, University of the Balearic Islands, Spain theorists provide a timely and insightful application of 21st century complex network science advances, as these natural mathematics gain deeper roots in conducive physical phenomena. (Search Neil Johnson, Pedro Manrique, for more findings of how an independent dynamics can even underlie violent conflicts.) The paper was written before the invasion, but can convey a vital illumination. As our 2020s postings now confirm (A Naturome Code, Earthuman Integrations), an actual organic genesis is found to be animated and constrained by an independent source script in exemplary, genetic-like effect for each and every instance. So into this real March madness, maybe concurrent Earthwise Learnings can dispense such edifications we so need.

During the last years, statistical physics has received an increasing attention as a framework for the analysis of real complex systems. However, this is less clear in the case of international political events, partly due to a difficulty in securing relevant quantitative evidence. Here we consider a detailed data set of violent events that took place in Ukraine since January 2021, and analyse their temporal and spatial correlations through entropy and complexity metrics, and functional networks. Results depict an unstable scenario, with events occurring in a non-random fashion, but with eastern-most regions functionally disconnected from the remainder of the country. (Abstract)

During the last decades, statistical physics concepts and tools have ceased being exclusive of this scientific field, for becoming standard approaches used in the analysis of numerous and heterogeneous real-world problems. To illustrate but a few examples, complex networks have become an essential asset in epidemics spreading models, neuroscience, and climate; along with biomedical systems from brain to heart dynamic. The reason for such success is possibly rooted in statistical physics' ability for decoupling the dynamical and observational scales; while a system may only be observable at the macro-scale, conclusions about the underlying micro-scale source can still be drawn. (1)

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