Introduction To Evolutionary Informatics - Brossura

Marks Ii, Robert J

Brossura

ISBN 10: 9813142146 ISBN 13: 9789813142145

Casa editrice: WSPC, 2017

Riassunto

Science has made great strides in modeling space, time, mass and energy in the recent years at a neck-breaking pace, accelerated by computational advancement. Yet little attention has been paid to the digital representation of this information and knowledge, in terms of storage capacity, information efficiency, reliability, and security.Extracted from a series of peer-reviewed papers published by the authors, Introduction to Evolutionary Informatics puts together results in information theory that now allow meaning and design difficulty to be measured, ranging across a wider spectrum of subjects from biology to bit units.Introduction to Evolutionary Informatics will appeal to enthusiasts in science, engineering and apologetics, as well as those interested in the information-theoretic components of closely examined evolution. The book is written at a level understandable to readers with knowledge of rudimentary high school math.

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Recensione

Introduction to Evolutionary Informatics is a lucid, entertaining, even witty discussion of important themes in evolutionary computation, relating them to information theory. It's far more than that, however. It is an assessment of how things might have come to be the way they are, applying an appropriate scientific skepticism to the hypothesis that random processes can explain many observed phenomena. Thus the book is appropriate for the expert and non-expert alike. --Donald Wunsch, Distinguished Professor and Director of the Applied Computational Intelligence Lab, Missouri University of Science & Technology, USA

Evolution requires the origin of new information. In this book, information experts Bob Marks, Bill Dembski, and Winston Ewert provide a comprehensive introduction to the models underlying evolution and the science of design. The authors demonstrate clearly that all evolutionary models rely implicitly on information that comes from intelligent design, and that unguided evolution cannot deliver what its promoters advertise. Though mathematically rigorous, the book is written primarily for non-mathematicians. I recommend it highly. --Jonathan Wells, Senior Fellow, Discovery Institute

Introduction to Evolutionary Informatics helps the non-expert reader grapple with a fundamental problem in science today: We cannot model information in the same way as we model matter and energy because there is no relationship between the metrics. As a result, much effort goes into attempting to explain information away. The authors show, using clear and simple illustrations, why that approach not only does not work but [that it also] impedes understanding of our universe. --Denyse O'Leary, Science Writer

L'autore

Robert J Marks II is Distinguished Professor of Engineering in the Department of Engineering at Baylor University, USA. Marks's professional awards include a NASA Tech Brief Award and a best paper award from the American Brachytherapy Society for prostate cancer research. He is Fellow of both IEEE and The Optical Society of America. His consulting activities include: Microsoft Corporation, DARPA, and Boeing Computer Services. He is listed as one of the 50 Most Influential Scientists in the World Today by TheBestSchools.org. (2014). His contributions include: the Zhao-Atlas-Marks (ZAM) time-frequency distribution in the field of signal processing, and the Cheung-Marks theorem in Shannon sampling theory.

Marks's research has been funded by organizations such as the National Science Foundation, General Electric, Southern California Edison, the Air Force Office of Scientific Research, the Office of Naval Research, the United States Naval Research Laboratory, the Whitaker Foundation, Boeing Defense, the National Institutes of Health, The Jet Propulsion Lab, Army Research Office, and NASA. His books include Handbook of Fourier Analysis and Its Applications (Oxford University Press), Introduction to Shannon Sampling and Interpolation Theory (Springer Verlag), and Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks (MIT Press) with Russ Reed. Marks has edited/co-edited five other volumes in fields such as power engineering, neural networks, and fuzzy logic. He was instrumental in defining the discipline of computational intelligence (CI) and is a co-editor of the first book using CI in the title: Computational Intelligence: Imitating Life (IEEE Press, 1994). His authored/coauthored book chapters include nine papers reprinted in collections of classic papers. Other book chapters include contributions to Michael Arbib's The Handbook of Brain Theory and Neural Networks (MIT Press, 1996), and Michael Licona et al.'s Evidence for God (Baker Books, 2010), Marks has also authored/co-authored hundreds of peer-reviewed conference and journal papers.

William A Dembski is Senior Research Scientist at the Evolutionary Informatics Lab in McGregor, Texas; and also an entrepreneur developing educational websites and software. He holds a BA in Psychology, MS in Statistics, PhD in Philosophy, and a PhD in Mathematics (awarded in 1988 by the University of Chicago, Chicago, Illinois, USA), and an MDiv degree from Princeton Theological Seminary (1996, New Jersey, USA). Dembski's work experience includes being an Associate Research Professor with the Conceptual Foundations of Science, Baylor University, Waco, Texas, USA. He has taught at Northwestern University, Evanston, Illinois, USA; the University of Notre Dame, Notre Dame, Indiana, USA; and the University of Dallas, Irving, Texas, USA. He has done postdoctoral work in mathematics with the Massachusetts Institute of Technology, Cambridge, USA; in physics with the University of Chicago, USA; and in computer science with Princeton University, Princeton, New Jersey, USA. He is a Mathematician and Philosopher. He has held National Science Foundation graduate and postdoctoral fellowships, and has published articles in mathematics, engineering, philosophy, and theology journals and is the author/editor of more than twenty books.

Winston Ewert is currently a Software Engineer in Vancouver, Canada. He is a Senior Research Scientist at the Evolutionary Informatics Lab. Ewert holds a PhD from Baylor University, Waco, Texas, USA. He has written a number of papers relating to search, information, and complexity including studies of computer models purporting to describe Darwinian evolution and developing information theoretic models to measure specified complexity.

Dettagli dell'edizione

• Editore: WSPC
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 9813142146
• ISBN 13: 9789813142145
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 330
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile