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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

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

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Reviews

“I am delighted to be able to recommend this amazingly broad and comprehensive four-volume handbook. Natural Computing is here to stay. It is already becoming a central theme on the borderline between computer science, mathematics and biology, and is poised to play a crucial role in 21st Century science. Grzegorz Rozenberg, besides being a superb scientist and thinker (and an astonishing magician too!), has the uncanny ability to bring together the best people and to somehow get them to contribute to important efforts. This handbook is one of his crowning achievements, and I salute both him and the wonderful result.”   [David Harel, Weizmann Institute of Science]

 

“The Handbook covers in a comprehensive and superb manner all central areas of natural computing. The term Natural Computing was coined by the Main Editor of the Handbook, Grzegorz Rozenberg, some thirty years ago to refer to human-designed computing inspired by nature, as well as computing actually taking place in nature. The main areas of the field (Cellular Automata, Neural Computation, Evolutionary Computation, Molecular Computation, Quantum Computation) are each subedited by top experts. Insights into other areas as well as hints to the future are provided in the part 'Broader Perspectives'. The number of contributors, 105, is amazing. The total result is an excellent massive set of four volumes that will constitute a unique source of reference for researchers and students for a long time to come.”   [Arto Salomaa, Academy of Finland]

 

“Natural sciences aim at discovery while technology seeks invention, thus the interplay of the two fosters creativity and is crucial for the advancement of knowledge. This timely Handbook is a vast effort to compile and relate what is known today about understanding nature through computation and about devising new models, techniques, and technologies of computation inspired by natural phenomena. As a pioneering and seminal work, it constitutes a magnificent entry point for those looking for an exciting research field, and I am sure it will become a reference pillar for the years to come.”   [Carme Torras, Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Barcelona]

 

“[The Handbook] is an achievement of excellent editing. The topics covered are widely disparate and there are dozens of authors involved, and yet the editors have produced a beautifully coordinated, balanced, and very readable resource. All the contributions are very well written, and moreover very well illustrated, and the individual chapters seem able to balance depth of coverage with accessibility. While the mathematical underpinning is rigorous, the clear text and the graphics make it possible for nonexperts to understand the topics with a reasonable effort. ... The many chapters in the various sections of this book show different aspects of the overall approach. Some chapters give a flavor of their topics in an informal manner, others explain the mathematics, while still others show how the topics can be applied. The emphasis throughout seems to be to explain the concepts without too many implementation details. The tone and clarity are consistent throughout, which makes it possible to read consecutive chapters without noticing any change in style or authorship. Each chapter also includes a good list of references for further study. ... I found it really inspiring to browse through all four volumes together, as it helps to get details of any one approach while having a view of the wider context. ... It provides a solid, easy-to-digest foundation for topics of increasing importance, and the grouping of chapters into related parts provides far more information than individual chapters could.”   [Sara Kalvala, ACM Computing Reviews, 2013]

 

“This work provides a solid presentation of both aspects of computing–natural and artificial–and serves as an important foundation and cross-fertilization for researchers in each area, although the emphasis is still primarily on nature-inspired artificial algorithms. … The book is inspirational in its coverage of the subject. It will be an indispensable tool for researchers and practitioners interested in developing nature-inspired algorithms and a valuable resource for research institutions. Summing Up: Highly recommended. Graduate students and above.” [J. Y. Cheung, Choice, Vol. 50 (5), January, 2013]