Advertisement

Evolution as Computation

DIMACS Workshop, Princeton, January 1999

  • Laura F. Landweber
  • Erik Winfree

Part of the Natural Computing Series book series (NCS)

Table of contents

  1. Front Matter
    Pages i-xv
  2. Thomas Bäck, Joost N. Kok, Grzegorz Rozenberg
    Pages 15-40
  3. Patricia K. Theodosopoulos, Theodore V. Theodosopoulos
    Pages 41-66
  4. James P. Crutchfield, Erik van Nimwegen
    Pages 67-94
  5. John R. Koza, Forrest H. Bennett III, David Andre, Martin A. Keane
    Pages 95-124
  6. Stephen J. Freeland
    Pages 125-139
  7. Guy Sella, David H. Ardell
    Pages 140-159
  8. Mark Ptashne, Alexander Gann
    Pages 179-200
  9. Andrzej Ehrenfeucht, David M. Prescott, Grzegorz Rozenberg
    Pages 216-256
  10. Laura F. Landweber, Lila Kari
    Pages 257-274
  11. Ron Weiss, George E. Homsy, Thomas F. Knight Jr.
    Pages 275-295
  12. Charles Ofria, Christoph Adami
    Pages 296-313
  13. Eric B. Baum, Igor Durdanovic
    Pages 314-332
  14. Back Matter
    Pages 333-333

About these proceedings

Introduction

The study of the genetic basis for evolution has flourished in this century, as well as our understanding of the evolvability and programmability of biological systems. Genetic algorithms meanwhile grew out of the realization that a computer program could use the biologically-inspired processes of mutation, recombination, and selection to solve hard optimization problems. Genetic and evolutionary programming provide further approaches to a wide variety of computational problems. A synthesis of these experiences reveals fundamental insights into both the computational nature of biological evolution and processes of importance to computer science. Topics include biological models of nucleic acid information processing and genome evolution; molecules, cells, and metabolic circuits that compute logical relationships; the origin and evolution of the genetic code; and the interface with genetic algorithms, genetic and evolutionary programming. This research combines theory and experiments to understand the computations that take place in cells and the combinatorial processes that drive evolution at the molecular level.

Keywords

algorithms evolution genetic algorithm genetic algorithms genome mutation optimization the origin

Editors and affiliations

  • Laura F. Landweber
    • 1
  • Erik Winfree
    • 2
  1. 1.Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonUSA
  2. 2.Computer Science and Computation and Neural SystemsCaltechPasadenaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-55606-7
  • Copyright Information Springer-Verlag Berlin Heidelberg 2002
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-642-63081-1
  • Online ISBN 978-3-642-55606-7
  • Series Print ISSN 1619-7127
  • Buy this book on publisher's site