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Introduction to Evolutionary Informatics

332pp    Apr 2017

  • ISBN: 978-981-3142-13-8 (hardcover)
  • ISBN: 978-981-3142-14-5 (softcover)
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Introduction to Evolutionary Informatics

By (author): Robert J Marks II (Baylor University, USA), William A Dembski (Evolutionary Informatics Lab, USA), Winston Ewert (Evolutionary Informatics Lab, USA)

"An honest attempt to discuss what few people seem to realize is an important problem. Thought provoking!"

Gregory Chaitin
Professor, Federal University of Rio de Janeiro, Brazil

"With penetrating brilliance, and with a masterful exercise of pedagogy and wit, the authors take on Chaitin's challenge, that Darwin's theory should be subjectable to a mathematical assessment and either pass or fail. Surveying over seven decades of development in algorithmics and information theory, they make a compelling case that it fails."

Bijan Nemati
Jet Propulsion Laboratory, California Institute of Technology, USA

"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

"Darwinian pretensions notwithstanding, Marks, Dembski, and Ewert demonstrate rigorously and humorously that no unintelligent process can account for the wonders of life."

Michael J Behe
Professor of Biological Sciences, Lehigh University, USA

"A very helpful book on this important issue of information. Information is the jewel of all science and engineering which is assumed but barely recognised in working systems. In this book Marks, Dembski and Ewert show the major principles in understanding what information is and show that it is always associated with design."

Andy C McIntosh
Visiting Professor of Thermodynamics, School of Chemical and Process Engineering, University of Leeds, LEEDS, UK

"Though somewhat difficult, Marks, Dembski and Ewert have done a masterful job of making the book accessible to the engaged and thoughtful layperson. I could not endorse this book more highly."

J P Moreland
Distinguished Professor of Philosophy, Biola University, USA

"This is an important and much needed step forward in making powerful concepts available at an accessible level."

Ide Trotter
Trotter Capital Management Inc.
Founder of the
Trotter Prize & Endowed Lecture Series on Information, Complexity and Inference (Texas A&M, USA)

"This is a fine summary of an extremely interesting body of work. It is clear, well-organized, and mathematically sophisticated without being tedious (so many books of this sort have it the other way around). It should be read with profit by biologists, computer scientists, and philosophers."

David Berlinski

"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