title: The Engine of Complexity: Evolution as Computation
author: John Mayfield
description: <i>The Engine of Complexity</i> is a well-written and erudite book of great importance. It promises to be the best single introduction to the informational concept of evolution, all while being clear and easy to read. (Geoffrey M. Hodgson, University of Hertfordshire)<br /><br />Wide ranging, ambitious, and clearly written, John E. Mayfield's <i>The Engine of Complexity</i> shows how information flowing down the ages in genes, thoughts, and words, guided only by the invisible hand of selection, has built everything from beetles and human brains to steam engines, space shuttles, and iPads. It will open your eyes to a different way of seeing the world. (Mark Pagel, University of Reading, author of <i>Wired for Culture: Origins of the Human Social Mind</i>)<br /><br />John E. Mayfield succeeds beautifully in making computational and biological concepts understandable to the non-expert reader. He suggests we are about to see a sea-change in our thinking with respect to how we view evolution in our society; he may be right, and his book is good reading to ready yourself for this potential change. (Alan G. Atherly, Iowa State University)<br /><br />An extraordinarily ambitious and broad volume. (Chris Adami <i>Quarterly Review of Biology</i>)
zlib_text: The Engine of Complexity
          Evolution  as 
          Computation
  John E. Mayfield
  
  The Engine of Complexity
  
  John E. MayfiEld
  The Engine 
  of Complexity
  Evolution as Computation
  columbia university press 
   
   
  new york
  
  Columbia University Press
  Publishers Since 1893
  New York Chichester, West Sussex
  cup.columbia.edu
  Copyright © 2013 John E. Mayfield
  All rights reserved
  Library of Congress Cataloging-in-Publication Data
  Mayfield, John E.
  The engine of complexity : evolution as computation / John E. Mayfield.
  pages cm
  Includes bibliographical references and index.
  ISBN 978-0-231-16304-0 (cloth : alk. paper)—ISBN 
  978-0-231-53528-1 (ebook)
  1.  Biology—Mathematical models. 2.  Evolution 
  (Biology)—Mathematical models. 3.  Biological control 
  systems—Mathematical models. 4.  Computational complexity.  I. Title.
  QH323.5.M389 2013
  570—dc23
  2013005728
  Columbia University Press books are printed on permanent and 
  durable acid-free paper.
  This book is printed on paper with recycled content.
  Pri