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Table of contents

  1. Front Matter
    Pages i-li
  2. Section I: Cellular Automata

    1. Front Matter
      Pages 1-1
    2. Jarkko J. Kari
      Pages 3-24
    3. Alberto Dennunzio, Enrico Formenti, Petr Kůrka
      Pages 25-75
    4. Marianne Delorme, Jacques Mazoyer
      Pages 77-122
    5. Véronique Terrier
      Pages 123-158
    6. Jacques Mazoyer, Jean-Baptiste Yunès
      Pages 159-188
    7. Nicolas Ollinger
      Pages 189-229
    8. Kenichi Morita
      Pages 231-257
    9. Siamak Taati
      Pages 259-286
  3. Section II: Neural Computation

    1. Front Matter
      Pages 333-333
    2. Hélène Paugam-Moisy, Sander Bohte
      Pages 335-376
    3. Xinbo Gao, Wen Lu, Dacheng Tao, Xuelong Li  
      Pages 377-399
    4. Seungjin Choi
      Pages 435-459
    5. G. Peter Zhang
      Pages 461-477
    6. Hwanjo Yu, Sungchul Kim
      Pages 479-506
    7. Kang Li, Guang-Bin Huang, Shuzhi Sam Ge
      Pages 507-531
    8. Joaquin J. Torres, Pablo Varona
      Pages 533-564
    9. Ke Chen, Lukasz A. Kurgan
      Pages 565-583
    10. Marc M. Van Hulle
      Pages 585-622
  4. Section III: Evolutionary Computation

    1. Front Matter
      Pages 623-623
    2. Kenneth De Jong
      Pages 625-635
    3. Darrell Whitley, Andrew M. Sutton
      Pages 637-671
    4. Günter Rudolph
      Pages 673-698
    5. Gary B. Fogel
      Pages 699-708
    6. Leonardo Vanneschi, Riccardo Poli
      Pages 709-739
    7. Silja Meyer-Nieberg, Hans-Georg Beyer
      Pages 741-814
    8. Günter Rudolph
      Pages 847-869
    9. Eckart Zitzler
      Pages 871-904
    10. Natalio Krasnogor
      Pages 905-935
    11. Tim Kovacs
      Pages 937-986
    12. Elena Popovici, Anthony Bucci, R. Paul Wiegand, Edwin D. De Jong
      Pages 987-1033
    13. Ofer M. Shir
      Pages 1035-1069
  5. Section IV: Molecular Computation

    1. Front Matter
      Pages 1071-1071
    2. Lila Kari, Shinnosuke Seki, Petr Sosík
      Pages 1073-1127
    3. Masami Hagiya, Satoshi Kobayashi, Ken Komiya, Fumiaki Tanaka, Takashi Yokomori
      Pages 1129-1184
    4. Yasubumi Sakakibara, Satoshi Hiyama
      Pages 1203-1232
    5. Robert Brijder, Mark Daley, Tero Harju, Nataša Jonoska, Ion Petre, Grzegorz Rozenberg
      Pages 1233-1280
    6. Masanori Arita, Masami Hagiya, Masahiro Takinoue, Fumiaki Tanaka
      Pages 1281-1318
    7. Gheorghe Păun
      Pages 1355-1377
  6. Section V: Quantum Computation

    1. Front Matter
      Pages 1379-1379
    2. Mika Hirvensalo
      Pages 1381-1412
    3. Časlav Brukner, Marek Żukowski
      Pages 1413-1450
    4. Jamie Smith, Michele Mosca
      Pages 1451-1492
    5. Kalle-Antti Suominen
      Pages 1493-1520

About this book

Introduction

Natural Computing is the field of research that investigates both human-designed computing inspired by nature and computing taking place in nature, i.e., it investigates models and computational techniques inspired by nature and also it investigates phenomena taking place in nature in terms of information processing.

Examples of the first strand of research covered by the handbook include neural computation inspired by the functioning of the brain; evolutionary computation inspired by Darwinian evolution of species; cellular automata inspired by intercellular communication; swarm intelligence inspired by the behavior of groups of organisms; artificial immune systems inspired by the natural immune system; artificial life systems inspired by the properties of natural life in general; membrane computing inspired by the compartmentalized ways in which cells process information; and amorphous computing inspired by morphogenesis. Other examples of natural-computing paradigms are molecular computing and quantum computing, where the goal is to replace traditional electronic hardware, e.g., by bioware in molecular computing. In molecular computing, data are encoded as biomolecules and then molecular biology tools are used to transform the data, thus performing computations. In quantum computing, one exploits quantum-mechanical phenomena to perform computations and secure communications more efficiently than classical physics and, hence, traditional hardware allows.

The second strand of research covered by the handbook, computation taking place in nature, is represented by investigations into, among others, the computational nature of self-assembly, which lies at the core of nanoscience, the computational nature of developmental processes, the computational nature of biochemical reactions, the computational nature of bacterial communication, the computational nature of brain processes, and the systems biology approach to bionetworks where cellular processes are treated in terms of communication and interaction, and, hence, in terms of computation.

We are now witnessing exciting interaction between computer science and the natural sciences. While the natural sciences are rapidly absorbing notions, techniques and methodologies intrinsic to information processing, computer science is adapting and extending its traditional notion of computation, and computational techniques, to account for computation taking place in nature around us. Natural Computing is an important catalyst for this two-way interaction, and this handbook is a major record of this important development.

Keywords

Amorphous computing Ant colony optimization Artificial chemistry Artificial immune systems (AIS) Artificial life Bacterial communication Biochemical computing Biochemical networks Biocomputing Biologically inspired algorithms Biologically inspired computing Biomolecular computing Bionetworks Bioware Brain processes Cell biology Cellular automata Coevolution Collision-based computing Computational system biology DNA computing Darwinian evolution Developmental biology Developmental computing Emergent computation Evolvable hardware Feedforward networks Gene assembly Gene regulatory network Genetics-based machine learning Genomic computer Independent component analysis (ICA) Information processing Kernel methods Membrane computing Memetic algorithms Molecular biology Molecular computation Molecular computing Morphogenesis Multiobjective optimization Nanocomputing Nanoscience Natural computation Natural computing Neural computation Neural networks Pattern recognition Process algebra Quantum algorithms Quantum complexity theory Quantum computation Quantum computing Quantum cryptography Quantum error correction Quantum information processing Quantum information theory Quantum mechanics Rough-fuzzy computing Self-assembly Self-organizing maps (SOMs) Simulated annealing Social computing Support vector machines (SVMs) Swarm intelligence Systems biology

Editors and affiliations

  • Grzegorz Rozenberg
    • 1
    • 2
  • Thomas Bäck
    • 3
  • Joost N. Kok
    • 4
  1. 1.LIACSLeiden UniversityLeidenThe Netherlands
  2. 2.Computer Science DepartmentUniversity of ColoradoBoulderUSA
  3. 3.LIACSLeiden UniversityLeidenThe Netherlands
  4. 4.LIACSLeiden UniversityLeidenThe Netherlands

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-92910-9
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-92909-3
  • Online ISBN 978-3-540-92910-9
  • Buy this book on publisher's site
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