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.

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

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