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Immunocomputing

Principles and Applications

  • A. O. Tarakanov
  • V. A. Skormin
  • S. P. Sokolova
Book

Table of contents

  1. Front Matter
    Pages i-xi
  2. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 1-12
  3. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 13-39
  4. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 41-60
  5. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 61-82
  6. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 83-112
  7. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 113-144
  8. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 145-182
  9. A. O. Tarakanov, V. A. Skormin, S. P. Sokolova
    Pages 183-184
  10. Back Matter
    Pages 185-193

About this book

Introduction

Overview This book introduces immunocomputing (Ie) as a new computing approach that replicates the principles of information processing by proteins and immune networks. It establishes a rigorous mathematical basis for IC, consistent with recent findings in immunology, and it presents various applications of IC to specific computationally intensive real-life problems. The hardware implementation aspects of the IC concept in an immunocomputer as a new kind of computing medium and its potential connections with modem biological microchips (biochips) and future biomolecular computers (biocomputers) are also discussed. All biological systems at the cellular and biomolecular levels are sophisticated mechanisms honed to perfection by millions of years of evolution, and their exploration provides inspiration for various novel concepts in science and engineering. Of these systems, however, only two types, the neural system and the immune system of the vertebrates, possess the extraordinary capabilities of "intellectual" information processing, which include memory, the ability to learn, to recognize, and to make decisions with respect to unknown situations. The potential of the natural neural system as a biological prototype of a computing scheme has already been utilized intensively in computer science through the mathematical and software models of artificial neural networks (ANN) and their hardware implementation in neural computers (see, e.g., Haykin, 1999; Wasserman, 1990).

Keywords

Hardware Mathematica artificial intelligence cognition computer computer science evolution information information processing intelligence knowledge modeling network networks pattern recognition

Authors and affiliations

  • A. O. Tarakanov
    • 1
  • V. A. Skormin
    • 2
  • S. P. Sokolova
    • 1
  1. 1.St. Petersburg Institute for InformaticsRussian Academy of SciencesSt. PetersburgRussia
  2. 2.Watson SchoolBinghamton UniversityBinghamtonUSA

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