Introduction To Evolutionary Informatics

Science has made great strides in modeling space, time, mass and energy. Yet little attention has been paid to the precise representation of the information ubiquitous in nature.Introduction to Evolutionary Informatics fuses results from complexity modeling and information theory that allow both meaning and design difficulty in nature to be measured in bits. Built on the foundation of a series of peer-reviewed papers published by the authors, the book is written at a level easily understandable to readers with knowledge of rudimentary high school math. Those seeking a quick first read or those not interested in mathematical detail can skip marked sections in the monograph and still experience the impact of this new and exciting model of nature's information.This book is written for enthusiasts in science, engineering and mathematics interested in understanding the essential role of information in closely examined evolution theory.

Review :
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" 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" 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" 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 desi -- 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 c -- Denyse O'Leary, Science Writer "Denyse O'Leary, Science Writer" 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 tha -- Donald Wunsch "Distinguished Professor and Director of the Applied Computational Intelligence Lab, Missouri University of Science & Technology, 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 "David Berlinski" 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)" 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" 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"