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III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator LifescapeC. The Information Computation Turn Tkacik, Gasper and William Bialek. Information Processing in Living Systems. arXiv:1412.8752. Institute of Science and Technology Austria, and Princeton University physicists opine that in some deep way the universe is engaged in the optimization of information content. In this view, could one say this endeavor has reached its crucial stage of its conscious recognition by the human/Earth phenomenon. Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been possible to measure, directly, the flow of information in biological networks, or more generally where information theoretic ideas have been used to guide the analysis of experiments. Systems of interest range from single molecules (the sequence diversity in families of proteins) to groups of organisms (the distribution of velocities in flocks of birds), and all scales in between. Many of these analyses are motivated by the idea that biological systems may have evolved to optimize the gathering and representation of information, and we review the experimental evidence for this optimization, again across a wide range of scales. (Abstract) Vallverdu, Jordi, ed. Thinking Machines and the Philosophy of Computer Science. Hershey, PA: Information Science Reference, 2010. A large volume of proceedings from the Seventh European Conference on Computing and Philosophy held in Barcelona, July 2009. Five sections span Philosophy of Information, Philosophy of Computer Science, Computer and Information Ethics, Simulating Reality?, and Intersections, wherein substantive papers attempt to accommodate and assimilate the 21st century turn to a generative natural realm of software-like “information.” Along with Gordana Dodig-Crnkovic noted above, Walter Riofrio’s “On Biological Computing, Information and Molecular Networks,” “Computing, Philosophy and Reality” by Joseph Brenner, and Klaus Mainzer’s “Challenges of Complex Systems in Cognitive and Complex Systems,” among others, are of much interest.
Varn, Dowman and Jim Crutchfield.
What did Erwin Mean? The Physics of Information from the Materials Genomics of Aperiodic Crystals & Water to Molecular Information Catalysts & Life.
Philosophical Transactions of the Royal Society.
Forthcoming, October,
2015.
The paper by UC Davis, Complexity Sciences Center, physicists is online at arXiv:1510.02778. It is also a summary of Jim Crutchfield’s thirty year complex systems endeavor which began at the Santa Fe Institute. At the outset, the contribution ought to be joined with other domains from quantum to social to cosmic as they each and all become reconceived as dynamic, self-organizing networks. Now even their ground phase of “inorganic” passive matter can be seen to possess these same qualities. An historic path is traced from Erwin Schrodinger’s (1887-1961) 1940’s book What is Life?, which posited that organisms and physical nature are both necessarily suffused by an informative materiality, to this mid 2010s collaborative confirmation. Walker, Sara Imari. Top-Down Causation and the Rise of Information in the Emergence of Life. Information. 5/3, 2014. The Arizona State University and ASU Beyond Center physicist and astrobiologist, with colleagues Paul Davies, George Ellis, and others, explains the presence and role of algorithmic processes that serve to originate and drive a complexifying evolution. The approach does remain within the default model of software programs and hardware manifestations. But by this view, living systems can be joined with, and seen as an inherent result of, a fundamentally spontaneous materiality. Through her discussions with Oxford University mathematician Chiara Marletto, this vivifying scenario is seen akin to David Deutsch’s “constructor” version. In any event, a natural, cosmic reality is engaged and articulated that is composed as a doubleness of a mathematical source, and the overt organic entities along with our decipherment which it generates. See also the author's 2015 paper The Descent of Math at arXiv:1505.00312. Biological systems represent a unique class of physical systems in how they process and manage information. This suggests that changes in the flow and distribution of information played a prominent role in the origin of life. Here I review and expand on an emerging conceptual framework suggesting that the origin of life may be identified as a transition in causal structure and information flow, and detail some of the implications for understanding the early stages chemical evolution. (Abstract) Walker, Sara Imari, et al, eds. From Matter to Life: Information and Causality. Cambridge: Cambridge University Press, 2017. With Paul Davies and George Ellis as coeditors, this significant collection gathers current notice across many areas of an innately fertile cosmos from which arise sapient organisms. The project began as a 2014 Information, Causality and the Origin of Life workshop at Arizona State University and has now grown to this volume. Its significant theme is an addition of an informational quality and vector, aka J. A. Wheeler’s “It from Bit,” as a novel explanatory source and agency. Wide-ranging considerations are engaged in chapters such as Constructor Theory of Information and Life by Chiara Marletto, Digital and Analogue Information in Organisms by Denis Noble, Causality, Information, and Biological Computation by Hector Zenil, et al, Life’s Informational Hierarchy by Jessica Flack, Major Transitions in Political Order by Simon Dedeo, and especially (How) Did Information Emerge? by Anne-Marie Grisogono. These and more are a stellar array of “methinks” views, but one wonders if an actual “cosmic elephant,” a phenomenal presence on its own, can be imagined and allowed, as some contributors have denied elsewhere. A common translation from many technical abstractions would help, and as this site attempts, a witness of this generative source as a natural, uniVerse to human genetic code. Recent advances suggest that the concept of information might hold the key to unravelling the mystery of life's nature and origin. Fresh insights from a broad and authoritative range of articulate and respected experts focus on the transition from matter to life, and hence reconcile the deep conceptual schism between the way we describe physical and biological systems. A unique cross-disciplinary perspective, drawing on expertise from philosophy, biology, chemistry, physics, and cognitive and social sciences, provides a new way to look at the deepest questions of our existence. This book addresses the role of information in life, and how it can make a difference to what we know about the world. Witzany, Gunther. Can Mathematics Explain the Evolution of Human Language? Communicative & Integrative Biology. 4/5, 2011. As another example of what our second decade of the 21st century can reveal as not before, the German geneticist, linguist, and philosopher cites three prime informational agencies – molecular nucleotide codes, literal communication, and their innate source in mathematical materialities. After years of their separate study and elucidation, a common affinity can now be affirmed between them, as if a single, manifest, ramifying program. Investigation into the sequence structure of the genetic code by means of an informatic approach is a real success story. The features of human language are also the object of investigation within the realm of formal language theories. They focus on the common rules of a universal grammar that lies behind all languages and determine generation of syntactic structures. This universal grammar is a depiction of material reality, i.e., the hidden logical order of things and its relations determined by natural laws. Therefore mathematics is viewed not only as an appropriate tool to investigate human language and genetic code structures through computer science based formal language theory but is itself a depiction of material reality. (516) Wolfram, Stephen. Is the Universe Like π or Ω? Dinneen, Michael, et al, eds. Computation, Physics, and Beyond. Berlin: Springer, 2012. In these proceedings of an International Workshop on Theoretical Computer Science held in Auckland, New Zealand, February, 2012, the wizardly founder of cellular automata, Mathematica and Wolfram Alpha suites, and author of A New Kind of Science, provides a succinct cosmic reality check. To be or not to be is posed by the Pi ratio for a comprehensible nature, versus Gregory Chaitin’s Omega number of an “uncomputable” universe. After many years now, it is said that standard particle physics is inadequate, does not contain gravity, string theories are no help. But in our computer age, if extant existence could be imagined as the result of a programmatic source, a software/hardware model, then a plausible explanation may be at hand. Indeed, in this capsule Wolfram well expresses the informational – computational turn. Moving on, could this be a bridge from the old Ptolemaic physics, through this abstract, machine doubleness, and cross over to an organic, procreative universe, to the witness and admission of an essential genotype and phenotype? I often wonder what it will be like if we actually do find that one of these simple programs can reproduce our universe. In a sense it will be a very anti-Copernican moment. For ever since Copernicus, we have repeatedly been confronted with ways in which we are not special. Our planet is not at the center of the universe. And so on. But if our universe is a simple one in the space of all possible universes, then it would seem that in that way we are in fact special. (317-318) Wolfram, Stephen. Talking about the Computational Future at SXSW 2013. blog.stephenwolfram.com/2013/03/talking-about-the-computational-future-at-sxsw-2013. A presentation given at the South by Southwest Conferences & Festivals, March 8-17, in Austin, Texas, available at SW’s Blog site in both video and illustrated text. For a public audience, a ten year retrospective of the polymath’s treatise A New Kind of Science, and a good introduction into these fertile imaginations of cellular automata. Stephen recounts how in the 1980s he became dissatisfied with the limitations of mechanical physics, and wondered if a realm of natural programs might actually be operating that serve to generate an evolutionary complexity and we peoples to figure it out. After 300 years of being dominated by Newton-style equations and math, the frontiers are definitely now going to simple programs and the new kind of science. But there’s still one ultimate app out there to be done: to figure out the fundamental theory of physics — to figure out how our whole universe works. It’s kind of tantalizing. We see these very simple programs, with very complex behavior. (An image of a lacey, network spacetime is next.) A giant network of nodes, that make up space a bit like molecules make up the air in this room. Well, you can start just trying possible programs that create such things. Each one is in a sense a candidate universe. Yang, Xin-She. Nature-Inspired Optimization Algorithms. Amsterdam: Elsevier, 2014. In our context of a worldwide learning project, the adoption of iterative methods such as Bayesian statistics, computational evolution, Markov processes, genetic algorithms, decision or game theory, and universal Darwinism seems to imply a dynamic cosmic development as some manner of self-selective maximization. This latest volume by the Middlesex University, London computer scientist and scholar provides as an extensive review of these mathematical programs at their generative work. After describing algorithmic programs, it goes on to biomimetic firefly, cuckoo search, bat, flower pollination, ant, bee, and particle swarm versions in use today. Their procedural operations are then perceived as a natural self-organization whence many agents interact by common rules to achieve a better fitness. To reflect, might we focus our own efforts to achieve a universe to humanity optimum? And could it all be a natural genetic code that emerges with evolution and meant to pass to our reception and continuance? Might one say therefore choose Earth? In essence, an algorithm is a step-by-step procedure of providing calculations or instructions. Many algorithms are iterative. The actual steps and procedures depend on the algorithm used and the context of interest. However, in this book, we mainly concern ourselves with the algorithms for optimization, and thus we place more emphasis on iterative procedures for constructing algorithms. (1) In essence, a genetic algorithm (GA) is a search method based on the abstraction of Darwinian evolution and natural selection of biological systems and representing them in the mathematical operators: crossover or recombination, mutation, fitness, and selection of the fittest. (17) Zenil, Hector, ed. A Computable Universe: Understanding and Exploring Nature as Computation. Singapore: World Scientific, 2012. Due by June, a contribution to Alan Turing Centenary celebrations edited by the University of Sheffield computer scientist. The result is a compendium upon the welling integration of physics and information. A foreword by Roger Penrose is followed by four sections: Foundations, Universality & Early Models; Physics, Computation & and the Computation of Physics; Computation in Nature & the World; The Quantum & Computation. Salient chapters may be “What is Ultimately Possible in Physics” by Stephen Wolfram, “The Universe as a Quantum Computer,” Seth Lloyd, and Matthew Szudzik’s “The Computable Universe Hypothesis.” The editor's opening chapter, noted in Anthropic Principle, is available at arXiv:1206.0376. The Penrose preface is also on this site. From Zenil’s own page http://www.mathrix.org/zenil can be accessed recent papers indicative of this theory and movement.
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