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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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III. Ecosmos: A Fertile, Habitable, Solar-Bioplanet Lifescape

D. Natural Econsciousness and Ecognition

Ulanowicz, Robert. Ecological Clues to the Nature of Consciousness. Entropy. 22/6, 2020. The veteran theoretical ecologist (search) was at the University of Maryland Center for Environmental Sciences for many years where, among other projects, he served as a caretaker of Chesapeake Bay. In 1987 Bob and I had lunch with Ilya Prigogine at a conference. In this paper he illumes that Integrated Information and Global Workspace theories of cerebral function with regard to knowing awareness can have an affinity to similar environmental principles and vitalities.

Some dynamics associated with consciousness are shared by other complex macroscopic living systems. Autocatalysis, an active agency in ecosystems, imparts to them a centripetality, the ability to attract resources. It is likely that autocatalysis in the central nervous system gives rise to the phenomenon of selfhood. Similarly, a coherence domain, as constituted in terms of bi-level coordination in ecosystems, stands as an analogy to the simultaneous access the mind has to available information. The result is the feeling that one’s surroundings are present to the individual all at once. Similar research in other fields suggests empirical approaches to the study of consciousness in humans and other higher animals. (Abstract)

Van der Helm, Peter. Simplicity in Vision: A Multidisciplinary Account of Perceptual Organization. Cambridge: Cambridge University Press, 2014. A University of Leuven, Belgium, psychologist contends that as sentient sight arises through an intense “veridicality,” the presence of universal algorithmic and holographic principles can provide a coherent explanation. See also his Transparallel Mind: Classical Computing with Quantum Power by the author at arXiv:1404.2267.

Perceptual organization is the neuro-cognitive process that enables us to perceive scenes as structured wholes consisting of objects arranged in space. Simplicity in Vision explores the intriguing idea that these perceived wholes are given by the simplest organizations of the scenes. Peter A. van der Helm presents a truly multidisciplinary approach to answer fundamental questions such as: Are simplest organizations sufficiently reliable to guide our actions? What is the nature of the regularities that are exploited to arrive at simplest organizations? To account for the high combinatorial capacity and speed of the perceptual organization process, he proposes transparallel processing by hyperstrings. This special form of distributed processing not only gives classical computers the extraordinary computing power that seemed reserved for quantum computers, but also explains how neuronal synchronization relates to flexible self-organizing cognitive architecture in between the relatively rigid level of neurons and the still elusive level of consciousness.

Vanchurin, Vitaly. The World as a Neural Network. arXiv:2008.01540. A Russian-American, University of Minnesota physicist continues his frontier studies about a cognitive property that the whole cosmos appears to possibly have. As informed by AI deep machine learning advances, a working hypothesis is that on the most fundamental level the dynamics of the entire universe is described by a microscopic neural network which undergoes a learning evolution. A further result that this edification can be seen in a thermodynamic way as opposed to dissipative entropy. This knowledge gaining counter course is then dubbed a second law of learning. See also Towards a Theory of Machine Learning by VV at 2004.09280 and search for several later entries with colleagues.

We discuss a possibility that the entire universe on its most fundamental level is a neural network. We identify two different types of dynamical degrees of freedom: "trainable" variables (e.g. bias vector or weight matrix) and "hidden" variables (e.g. state vector of neurons). We first consider stochastic evolution of the trainable variables to argue that near equilibrium their dynamics is well approximated by Madelung equations and by Hamilton-Jacobi equations. This shows that the trainable variables can indeed exhibit classical and quantum behaviors with the state vector of neurons representing the hidden variables. This shows that the learning dynamics of a neural network can indeed exhibit approximate behaviors described by both quantum mechanics and general relativity. We also discuss a possibility that the two descriptions are holographic duals of each other. (Abstract excerpt)

Vertosick, Frank. The Genius Within. New York: Harcourt, 2002. A neurosurgeon describes an intelligence inherent in every domain of life from enzyme networks to microbial communities, the immune system, brains, ecosystems, the world wide web and a living planet Gaia. This occurs because in each case many entities interact for their own purposes, which then self-organizes into a composite cognition.

Evolution and intelligence are one and the same process. (175)

Wang, Zheng, et al. The Potential of Using Quantum Theory to Build Models of Cognition. Topics in Cognitive Science. Online September, 2013. An Introduction by psychologists Wang, Jerome Busemeyer, Harald Atmanspacher, and Emmanuel Pothos for a special issue to explore possible correspondences between such basic physical phenomena and our risen human cerebration. See especially “Concepts and Their Dynamics: A Quantum-Theoretic Modeling of Human Thought” by Diederik Aerts, Liane Gabora and Sandro Sozzo.

Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability theory and a concrete example is provided to illustrate how a quantum cognitive model can be developed to explain paradoxical empirical findings in psychological literature. (Wang, et al Abstract)

We analyze different aspects of our quantum modeling approach of human concepts and, more specifically, focus on the quantum effects of contextuality, interference, entanglement, and emergence, illustrating how each of them makes its appearance in specific situations of the dynamics of human concepts and their combinations. We point out the relation of our approach, which is based on an ontology of a concept as an entity in a state changing under influence of a context, with the main traditional concept theories, that is, prototype theory, exemplar theory, and theory theory. We ponder about the question why quantum theory performs so well in its modeling of human concepts, and we shed light on this question by analyzing the role of complex amplitudes, showing how they allow to describe interference in the statistics of measurement outcomes, while in the traditional theories statistics of outcomes originates in classical probability weights, without the possibility of interference. The relevance of complex numbers, the appearance of entanglement, and the role of Fock space in explaining contextual emergence, all as unique features of the quantum modeling, are explicitly revealed in this article by analyzing human concepts and their dynamics. (Aerts, et al Abstract)

Weiss, Kenneth and Anne Buchanan. The Intelligent Egg, and How It Got That Way: From Genes to Genius in a Few Easy Lessons. Evolution: Education and Outreach. 5/2, 2012. This publication is edited by Niles and Gregory Eldridge to “promote accurate understanding and comprehensive teaching of evolutionary theory for a wide audience,” and is now available as a Springer Open Journal. This account of an innate, ascendant mindfulness by the Penn State anthropologists and authors, traces life’s formidable, active cognizance to such ovular cellular realms. In regard, evolutionary development is much about “signaling” between entities at every stage for survival, reproduction and prosperity, as if life is trying to narrate itself into risen being. A Figure shows “The cell as an intelligence agency” with a bounded vesicle with internal vitals of nucleus, mitochondria, cytoplasm, and so on. And if might we avail, nature offers a fine model for its latest phase of ecovillage social proto-cells (search section).

A seed has no flowers or leaves, and an egg no fingers or lungs. Yet plants and animals not only have these things but they resemble their parents in detail throughout their bodies. Something is inherited, but what is it? Life is based on the activities of cells. An organism has large numbers of them — a human has trillions! Cells live as separate units, which enables them each to do its own thing within its particular organ, but to be an organism they must work together. A cell can only detect its immediate local environment, but that includes various kinds of signals or information from nearby or far away within the body —or even from the external environment. It is by being local but responding globally in this way that an egg becomes an organism, an organism manages its way through life, and organisms make up species and ecosystems that interact with each other. The evolution of these abilities has produced the glorious array of living forms that populate the world. In these ways, an egg may have no thoughts but is a highly intelligent being. (Abstract)

In the senses we’ve considered here, life is a single phenomenon that one could say is an ‘intelligent’ information-exchanging phenomenon. If embryology is divergence of information by differential usage of its genes in the tree of cellular descent from the single ancestral fertilized egg, then evolution is divergence of the information (genomes) among individuals in a tree of descent from a common ancestor. Among the related cells within an embryo, it is the usage of a given set of genes that differentiates the branches. Among related species, it is the set of genes that varies. Thus information has been accumulating among different lineages of plant and animal life over evolutionary times, while information usage differences accumulate in different cell lineages within an individual lifetime. In that sense, all of life is intelligent in the same way that an egg is. (201-202)

The idea that life is all about signaling is somewhat different from the widespread view that Darwin’s theory of evolution is at the core of life. Evolution is an important fact, which explains much about the variation we see now, and from the past, about life on Earth. Evolution is usually viewed, in a rather exaggerated way, as being all about competition. But life is much, much more about the interaction of cells and the information they exchange — that is, about cooperation — than it is about competition. Evolution helps specify the combinations that work in given times and places in life’s history, but it is screening on successful cooperation more than on successful competition. (202)

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