III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet Lifescape

C. The Information Computation Turn

Marijuan, Pedro. Bioinformation: Untangling the Networks of Life. BioSystems. 64/1-4, 2002. An insightful paper on the persistent, dynamic role of informative templates in organic development.

Life is knowledge-bearing matter…the story is about genes or Darwinian replicators that embody knowledge about their niche, laws of nature included, causing the niche to keep that knowledge in existence. (112) We may argue, following Gell-Mann, that from the point of view of information, this organization of the living cell represents the emergence of a very special ‘complex adaptive system’: it is a quasi-universal problem solver based on the cytoplasm-genome representation interrelationship. (114)

Marijuan, Pedro. Knowledge Recombination on the Informational Adaptability of cells, Nervous Systems, and Societies. International Journal on Information Theories and Applications. 18/1, 2011. A veteran theorist, Pedro Marijuan (search) is in the Bioinformation and Systems Biology Group, Aragon Institute of Health Sciences, Zaragoza, Spain. The journal is based in Bulgaria and offers such premier articles with full online access. Also in the issue are “Emergent Information: Some System-Theoretical Considerations About an Integrative Information Concept” by Wolfgang Hofkirchner, “Information as a Natural and Social Operator” Joseph Brenner and Mark Burgin, and “From Philosophy to Theory of Information” by Marcin Schroeder. As Marijuan well states, there is just some kind of instructive, creative quality that is nature’s essential source which needs to be entered and articulated. And as many papers in this section and throughout the site, it begs to be seen, in translation, much as an innate parents to children “genetic code” of a procreative family cosmos.

Actually the growth of informational complexity of cells, nervous systems, and societies along their respective evolutionary, ontogenetic, and historical trajectories has been based on the cumulative consequences of knowledge recombination phenomena. However, the recognition of this commonality has been obscured, among other causes, by the structural and dynamic heterogeneity of repositories in the different informational entities, and by being subject of quite separated scientific disciplines: molecular and evolutionary biology, cognitive neurodynamics, philosophy of science/”geography” of science. In the extent to which such commonalities may be elucidated from a new vantage point, it would help in the development of information science itself, as well as in the pragmatics of education, in the social organization of science, and in the research effort of contemporary societies. Finally, the new term of “scientomics” is proposed in order to capture the knowledge combinatory processes and disciplinary mixings within the sciences. (Abstract)

Marijuan, Pedro. The Advancement of Information Science. TripleC. 7/2, 2009. In a special section “What is Really Information? An Interdisciplinary Approach,” the Spanish systems bioinformatician has been a pioneer advocate for the interpretation of life from cosmos to children as most characterized, both in essential origin and constant discourse, by a quality of and proclivity for constructive communication. See in regard his earlier “Information and Life: Towards a Biological Understanding of Informational Phenomena” in this journal (2/1, 2004), and other postings herein.

The advancement of a new scientific perspective, information science, devoted to the study of the vast field of informational phenomena in nature and society, implies putting together a number of cognizing domains which are presently scattered away in many other disciplines. Comparable to previous scientific revolutions spurred by thermodynamics and quantum mechanics, it would be time to go beyond the classical discussions on the concept of information, and associated formal theories, and advance a “new way of thinking”. Cells, Brains, Societies, and Quantum information would be crucial arenas for this discussion. Rather than hierarchy, reduction, or unification, the catchword is unending recombination... A mature information science should offer a new panoramic view on the sciences themselves and contribute to achieve social adaptability & sustainability. (Abstract, 369)

Markopoulou, Fotini. The Computing Spacetime. arXiv:1201:3398. Posted January 2012, wherein the Perimeter Institute, University of Waterloo, and Max Planck Institute physicist provides a cogent overview of this Turing turn lately gaining adherents, substance, and press, as this section reports. By way of her quantum theory interests, the admission of an informational quality, “a universe thought of as software,” will help physics unify gravity and relativity, and resolve further issues. As she writes “The universe as Computation suggests a new kind of unification: physical systems and their dynamics can be represented in terms of their information content.”

The idea that the Universe is a program in a giant quantum computer is both fascinating and suffers from various problems. Nonetheless, it can provide a unified picture of physics and this can be very useful for the problem of Quantum Gravity where such a unification is necessary. In previous work we proposed Quantum Graphity, a simple way to model a dynamical spacetime as a quantum computation. In this paper, we give an easily readable introduction to the idea of the universe as a quantum computation, the problem of quantum gravity, and the graphity models. (Abstract, 1)

Quantum information theory has given a new and interesting twist on the Universe as a Computation. A common idea that is advocated by many practitioners in this field is that everything fundamentally is information, an old idea that can be traced at least back to Wheeler's influential it from bit. In that view, all interactions between physical systems in the universe are instances of information processing, and the information involved in those processes is more primary than the physical systems themselves. Instead of thinking of particles as colliding, we should think of the information content of the particles being involved in a computation. (2)

Markos, Anton, et al. Life As Its Own Designer. Berlin: Springer, 2009. Six university natural philosophers from the Czech Republic attempt a recast of Darwinian evolution so as to emphasize biosemiotic communication as its defining, self-organizing motive quality. In such a view living beings become narrative “co-creators” of their own worlds. You get the impression that the authors have something important to say, but this mostly gets lost in disjointed chapter essays and academic jargon. But there is a distinction impression that these thinkers, and many others, are simply trying to evoke and describe a real universe to human genetic code.

Marshall, William, et al. Black-Boxing and Cause-Effect Power. arXiv:1608.03461. With Larissa Albantakis and Giulio Tononi, University of Wisconsin psychologists expand upon the Tononi’s popular Integrated Information theories, with many colleagues, to argue that a reductive method to study physical substrates is ever inadequate. Rather by these lights, natural, Earthly evolution seems distinguished by a progressive tendency toward and increase of informational, knowledgeable qualities. A companion paper is Quantifying Causal Emergence Shows that Macro can Beat Micro by Erik Hoel with Albantakis and Tononi (PNAS110/19790, 2014).

McQuillan, Dan. Data Science as Machinic Neoplatonism. Philosophy and Technology. Online August, 2017. As a way to appreciate and avail this late version of an immanate source code, a Goldsmiths, University of London lecturer on creative and social computing reaches across the millennia to its perennial witness, as the quotes cite. An original glimpse came from Greek sages who indeed saw worldly abidance as such a double domain. A deep informative cause and exemplary world continued over the centuries into the Renaissance of Copernicus, Galileo, and Newton (search Margaret Cavendish for a “vitalistic materialism”). The author’s aim is to rescue this algorithmic scheme from a mechanical sterility unto a “machine learning for the People” via “participatory agency.”

Data science is not simply a method but an organising idea. Understanding data science requires an appreciation of what algorithms actually do; in particular, how machine learning learns. But attempts to stem the tide have not grasped the nature of data science as both metaphysical and machinic. Data science strongly echoes the neoplatonism that informed the early science of Copernicus and Galileo. It appears to reveal a hidden mathematical order in the world that is superior to our direct experience. But a counterculture of data science must be material as well as discursive. Karen Barad’s idea of agential realism can reconfigure data science to produce both non-dualistic philosophy and participatory agency. (Abstract excerpts)

What would it mean to say that data science is neoplatonic? The philosophical school of Platonism is committed to a two-world metaphysics. Behind the world of the sensible, that which we experience through our senses, is the world of Form or the Idea. (7-8) As such, the world of the Idea is ontologically superior to the one we actually inhabit. For Plato and the neoplatonists, mathematics is the linimal realm between the imperfect and transitory world of the senses and the perfect and eternal of pure spirit. Mathematical relations concerning triangles and circles, for example, are true independently of any particular triangle or circle. (8)

Mediano, Pedro, et al. Greater than the Parts: A Review of the Information Decomposition Approach to Causal Emergence. arXiv:2111.06518. Eight senior systems theorists from the UK, USA and Canada including Henrik Jensen, Anil Seth and Fernando Rosas expand and deepen our Earthuman frontiers of discovering, quantifying and articulating the presence of a universal, independent, manifestly exemplified generative domain at each and every ecosmic scale and instance. A latest finesse of integrated information theory provides a mathematical measure whence the same form and flow, pattern and process of common node/link, entity/group complements repeats in kind. Key cases are cellular automata, bird flocks, and cerebral cognition, which is then dubbed a “causal emergence.” Albeit a highly technical work, a similar reality with a likeness to genotype and phenotype gains vital credence. See also Beyond Integrated Information: A Taxonomy of Information Dynamics Phenomena by this collegial team at 1909.02297.

Emergence is a profound subject that straddles many scientific disciplines from galaxy formations all the way to how consciousness arises from the collective activity of neurons. Despite perceptions that some kind of intrinsic manifestation is underway, its scientific and conceptual study has suffered from a formalism basis that could guide collaborative discussions. Here we conduct a broad survey so to introduce a formal theory of causal emergence based on an information decomposition feature. As a result, information about a system's temporal evolution beyond its separate parts appears to reveal an ascendant path. This article provides a rigorous framework by which to assess the proposed approach in diverse scenarios. (Abstract excerpt)

Merrell, Floyd. Resemblance: From a Complementary Point of View? Sign Systems Studies. 38/1-4, 2010. In a issue about the title term, this paper can accompany Merrell’s 2010 book Entangling Forms, reviewed next, with its focus on this fluidly creative reciprocity of an emergent natural genesis. In earlier centuries, known as exemplarity, sympathy, emblematic, correlative, this perennial secret reveals a gender-based reflection between every entity, community, and strata. Merrell’s essay is then a postmodern paean to this yin-yang-ness in its constant, organically spiraling florescence toward self-individuation. And for our website, in the translation this begs, might one suggest that we are at last simply reading the presence and activity of nature’s parents to children genetic code?

However, as this essay unfolds, we shall note that everything is ‘multivalently’ and ‘nonlinearly’ interdependently interrelated to, and interactive with, everything else, which is to say that nothing is absolutely incommensurable or incompatible with anything else, but rather, complementarity is the watchword. (94)

Miguel-Tome, Sergio. The Influence of Computational Traits on the Natural Selection of the Nervous System. Natural Computing. Online March, 2018. A University of Salamanca, Spain neurotheorist argues that in retrospect life’s evolution has arrived at robust computational neural networks because they empowered a critical brain function of better predictability across animal kingdoms.

Mitchell, Melanie. Biological Computation. The Computer Journal. 55/7, 2012. In a special issue in honor of the Alan Turing Centenary, a Portland State University systems mathematician and author (Complexity: A Guided Tour) elucidates how this Turing turn is aiding a better appreciation of how living nature is distinguished and sustained by such an incarnate informational essence. See also in this edition “Natural Computation” by Erol Gelenbe and “Computation and Fundamental Physics” by David Bacon.

In this note we argue that biological computation is a process that occurs in nature, not merely in computer simulations of nature. (Abstract) In this article, the term biological computation refers to the proposal that living organisms themselves perform computations, and, more specifically, that the abstract ideas of information and computation may be key to understanding biology in a more unified manner. While there is some overlap among these different meldings of biology and computer science, it is only the study of biological computation that asks, specifically, if, how, and why living systems can be viewed as fundamentally computational in nature. (852)

This widespread interest in biological computation reflects a strong intuition that the notions of information and information processing are building blocks that will shed new light on how living systems operate and the common principles underlying their operation. Biology has long suffered from being a science of specific details rather than abstractions and general laws. The theory of evolution serves as one grand organizing principle, but biology still lacks a general theory of how adaptive functionality emerges from large collections of individual, decentralized components. (852)

How, for example, do insect colonies, composed of thousands to millions of individual insects, collectively make decisions and accomplish complex tasks that seem to require the communication and processing of colony‐wide information? How does the immune system, composed of trillions of cells and molecular components circulating in the body, collectively recognize patterns of infection and other organism-wide conditions, and collectively decide how to mount an appropriate response? How do the hundreds of billions of neurons in the brain work together to continually make sense of and respond to the opportunities and threats of the environment in real‐time? These questions cry out for a unified theory involving information, communication, and computation. (852)

Mora, Thierry, et al. JSP Special Issue on Information Processing in Living Systems. Journal of Statistical Physics. 162/5, 2017. French (Mora and Olivier Rivoire) and American (Luca Peliti) theorists introduce a survey of life’s communicative source as it lately becomes amenable with and rooted in physical phenomena. Some papers are Landauer in the Age of Synthetic Biology, Informations in Models of Evolutionary Dynamics, and Biological Implications of Dynamical Phases in Non-Equilibrium Networks.

Living systems are information-processing systems: they need to copy internal information, e.g., contained in their DNA, for producing their proteins—and regulating their production—or for reproducing. They also need to monitor their environment and their internal state, and to control their activity based on the collected informations. Trying to understand how living systems manage these tasks defines an area of questions at the cross-roads between statistical physics, information theory and biology. The contributions contained in the present Special Issue cover a wide-range of topics from information-dissipation trade-offs to statistical inference and issues of biological noise, hope to shed some light on these questions. (First paragraph)

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