Fundamentals of Natural Computing Basic Concepts, Algorithms, and Applications

ISBN-10: 1584886439
ISBN-13: 9781584886433
Edition: 2006
List price: $109.95
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Description: Natural computing brings together nature and computing to develop new computational tools for problem solving; to synthesize natural patterns and behaviors in computers; and to potentially design novel types of computers. Fundamentals of Natural  More...

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Book details

List price: $109.95
Copyright year: 2006
Publisher: CRC Press LLC
Publication date: 6/2/2006
Binding: Hardcover
Pages: 696
Size: 5.25" wide x 9.25" long x 1.50" tall
Weight: 2.332
Language: English

Natural computing brings together nature and computing to develop new computational tools for problem solving; to synthesize natural patterns and behaviors in computers; and to potentially design novel types of computers. Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications presents a wide-ranging survey of novel techniques and important applications of nature-based computing.This book presents theoretical and philosophical discussions, pseudocodes for algorithms, and computing paradigms that illustrate how computational techniques can be used to solve complex problems, simulate nature, explain natural phenomena, and possibly allow the development of new computing technologies. The author features a consistent and approachable, textbook-style format that includes lucid figures, tables, real-world examples, and different types of exercises that complement the concepts while encouraging readers to apply the computational tools in each chapter. Building progressively upon core concepts of nature-inspired techniques, the topics include evolutionary computing, neurocomputing, swarm intelligence, immunocomputing, fractal geometry, artificial life, quantum computing, and DNA computing.Fundamentals of Natural Computing is a self-contained introduction and a practical guide to nature-based computational approaches that will find numerous applications in a variety of growing fields including engineering, computer science, biological modeling, and bioinformatics.

From Nature to Natural Computing
Introduction
Motivation
A Small Sample of Ideas
The Philosophy of Natural Computing
The Three Branches: A Brief Overview
Computing Inspried by Nature
The Simulation and Emulation of Nature in Computers
Computing with Natural Materials
When to Use Natural Computing Approaches
Summary
Questions
References
Conceptualization
Introduction
Natural Phenomena, Models, and Metaphors
From Nature to Computing and Back Again
General Concepts
Individuals, Entities, and Agents
Parallelism and Distributivity
Interactivity
Connectivity
Stigmergy
Adaptation
Learning
Evolution
Feedback
Positive Feedback
Negative Feedback
Self-Organization
Characteristics of Self-Organization
Alternatives to Self-Organization
Complexity, Emergence, and Reductionism
Complexity
Emergence
Reductionism
Bottom-up vs. Top-down
Bottom-Up
Top-Down
Determinism, Chaos, and Fractals
Summary
Exercises
Questions
Thought Exercise
Projects and Challenges
References
Computing Inspired by Nature
Evolutionary Computing
Introduction
Problem Solving as a Search Task
Defining a Search Problem
Hill Climbing and Simulated Annealing
Hill Climbing
Simulated Annealing
Basic Principles of Statistical Thermodynamics
The Simulated Annealing Algorithm
From Statistical Thermodynamics to Computing
Example of Application
Evolutionary Biology
On the Theory of Evolution
Darwin's Dangerous Idea
Basic Principles of Genetics
Evolution as an Outcome of Genetic Variation Plus Selection
A Classic Example of Evolution
A Summary of Evolutionary Biology
Evolutionary Computing
Standard Evolutionary Algorithm
Genetic Algorithms
Roulette Wheel Selection
Crossover
Mutation
Examples of Application
A Step by Step Example: Pattern Recognition (Learning)
Numerical Function Optimization
Hill-Climbing, Simulated Annealing, and Genetic Algorithms
The Other Main Evolutionary Algorithms
Evolution Strategies
Selection
Crossover
Mutation
Evolutionary Programming
Selection
Mutation
Genetic Programming
Crossover
Mutation
Selected Applications from the Literature: A Brief Description
ES: Engineering Design
EP: Parameter Optimization
GP: Pattern Classification
From Evolutionary Biology to Computing
Scope of Evolutionary Computing
Summary
The Blind Watchmaker
Exercises
Questions
Computational Exercises
Thought Exercises
Projects and Challenges
References
Neurocomputing
Introduction
The Nervous System
Levels of Organization in the Nervous System
Neurons and Synapses
Networks, Layers, and Maps
Biological and Physical Basis of Learning and Memory
Artificial Neural Networks
Artificial Neurons
The McCulloch and Pitts Neuron
A Basic Integrate-and-Fire Neuron
The Generic Neurocomputing Neuron
Network Architectures
Single-Layer Feedforward Networks
Multi-Layer Feedforward Networks
Recurrent Networks
Learning Approaches
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Typical Anns and Learning Algorithms
Hebbian Learning
Biological Basis of Hebbian Synaptic Modification
Single-Layer Perceptron
Linear Separability
Simple Perceptron for Pattern Classification
Multiple Output Perceptron for Pattern Classification
Examples of Application
Adaline, the LMS Algorithm, and Error Surfaces
LMS Algorithm (Delta Rule)
Error Surfaces
Multi-Layer Perceptron
The Backpropagation Learning Algorithm
Universal Function Approximation
Some Practical Aspects
Biological Plausibility of Backpropagation
Examples of Application
Self-Organizing Maps
Self-Organizing Map Learning Algorithm
Biological Basis and Inspiration for the Self-Organizing Map
Examples of Applications
Discrete Hopfield Network
Recurrent Neural Networks as Nonlinear Dynamical Systems
Discrete Hopfield Network
Spurious Attractors
Example of Application
From Natural to Artificial Neural Networks
Scope of Neurocomputing
Summary
Exercises
Questions
Computational Exercises
Thought Exercises
Projects and Challenges
References
Swarm Intelligence
Introduction
Ant Colonies
Ants at Work: How an Insect Society Is Organized
Ant Foraging Behavior
Stigmergy
Ant Colony Optimization (ACO)
The Simple Ant Colony Optimization Algorithm (S-ACO)
General-Purpose Ant Colony Optimization Algorithm
Selected Applications from the Literature: A Brief Description
Scope of ACO Algorithms
From Natural to Artificial Ants
Clustering of Dead Bodies and Larval Sorting in Ant Colonies
Stigmergy
Ant Clustering Algorithm (ACA)
The Standard Ant Clustering Algorithm (ACA)
Selected Applications from the Literature: A Brief Description
Scope of Ant Clustering Algorithms
From Natural to Artificial Ants
Summary of Swarm Systems Based on Social Insects
Swarm Robotics
Foraging for Food
Clustering of Objects
Collective Prey Retrieval
Cooperative Box Pushing
Recruitment of Nestmates
Scope of Swarm Robotics
Summary of Swarm Robotics
Social Adaptation of Knowledge
Particle Swarm
Selected Applications from the Literature: A Brief Description
Optimization of Neural Network Weights
Numerical Function Optimization
Scope of Particle Swarm Optimization
From Social Systems to Particle Swarm
Summary of Particle Swarm Optimization
Summary
Exercises
Questions
Computational Exercises
Thought Exercises
Projects and Challenges
References
Immunocomputing
Introduction
The Immune System
Physiology and Main Components
Pattern Recognition and Binding
Adaptive Immune Response
Adaptation via Clonal Selection
Clonal Selection and Darwinian Evolution
Self/Nonself Discrimination
The Immune Network Theory
Adaptation and Learning via Immune Network
Danger Theory
A Broader Picture
Artificial Immune Systems
Representation
Evaluating Interactions
Immune Algorithms
Bone Marrow Models
Selected Applications from the Literature: A Brief Description
Evolution of the Genetic Encoding of Antibodies
Antigenic Coverage and Evolution of Antibody Gene Libraries
Generating Antibodies for Job Shop Scheduling
Negative Selection Algorithms
Binary Negative Selection Algorithm
Real-Valued Negative Selection Algorithm
Selected Applications from the Literature: A Brief Description
Network Intrusion Detection
Breast Cancer Diagnosis
Clonal Selection and Affinity Maturation
Forrest's Algorithm
Clonalg
Selected Applications from the Literature: A Brief Description
Pattern Recognition
Multimodal Function Optimization
Artificial Immune Networks
Continuous Immune Networks
Discrete Immune Networks
Selected Applications from the Literature: A Brief Description
A Recommender System
Data Compression and Clustering
From Natural to Artificial Immune Systems
Scope of Artificial Immune Systems
Summary
Exercises
Questions
Computational Exercises
Thought Exercises
Projects and Challenges
References
The Simulation and Emulation of Natural Phenomena in Computers
Fractal Geometry of Nature
Introduction
The Fractal Geometry of Nature
Self-Similarity
Some Pioneering Fractals
Dimension and Fractal Dimension
Scope of Fractal Geometry
Cellular Automata
A Simple One-Dimensional Example
Cellular Automata as Dynamical Systems
Formal Definition
Example of Application
Fractal Patterns
Scope of Cellular Automata
L-Systems
DOL-Systems
Turtle Graphics
Models of Plant Architecture
Scope of L-systems
Iterated Function Systems
Iterated Function Systems (IFS)
Deterministic Iterated Function System (DIFS)
Random Iterated Function System (RIFS)
Creating Fractals with IFS
Self-Similarity Revisited
Scope of IFS
Fractional Brownian Motion
Random Fractals in Nature and Brownian Motion
Fractional Brownian Motion
Scope of fBm
Particle Systems
Principles of Particle Systems
Basic Model of Particle Systems
Particle Generation
Particle Attributes
Particle Extinction
Particle Dynamics
Particle Rendering
Pseudocode and Examples
Scope of Particle Systems
Evolving the Geometry of Nature
Evolving Plant-Like Structures
Scope of Evolutionary Geometry
From Natural to Fractal Geometry
Summary
Exercises
Questions
Computational Exercises
Thought Exercises
Projects and Challenges
References
Artificial Life
Introduction
A Discussion about the Structure of the Chapter
Concepts and Features of Artificial Life Systems
Artificial Life and Computing Inspired by Nature
Life and Artificial Organisms
Artificial Life and Biology
Models and Features of Computer-Based Alife
Alife Systems as Complex (Adaptive) Systems
Examples of Artificial Life Projects
Flocks, Herds, and Schools
Discussion and Applications
Biomorphs
Discussion and Applications
Computer Viruses
Discussion and Applications
Synthesizing Emotional Behavior
Discussion and Applications
AIBO Robot
Discussion and Applications
Wasp Nest Building
Discussion and Applications
Creatures
Discussion and Applications
Artificial Fishes
Discussion and Applications
Turtles, Termites, and Traffic Jams
Predator-Prey Interactions
Termites
Traffic Jams
Slime-Mold
Discussion and Applications
Cellular Automata Simulations
The Game of Life
Langton's Loops
CAFUN
Framsticks
Architecture of the Framsticks and Its Environment
Evolving the Framsticks
Discussion and Applications
Scope of Artificial Life
From Artificial Life to Life-as-We-Know-It
Summary
Exercises
Questions
Computational Exercises
Thought Exercise
Projects and Challenges
References
Computing with New Natural Materials
DNA Computing
Introduction
Motivation
Basic Concepts from Molecular Biology
The DNA Molecule
Manipulating DNA
Filtering Models
Adleman's Experiment
Discussion
Lipton's Solution to the SAT Problem
Discussion
Test Tube Programming Language
The Unrestricted DNA Model
Examples of Application
An Extension of the Unrestricted DNA Model
The DNA Pascal
Formal Models: A Brief Description
Sticker Systems
Splicing Systems
Insertion/Deletion Systems
The PAM Model
Universal DNA Computers
Scope of DNA Computing
From Classical to DNA Computing
Summary and Discussion
Exercises
Questions
Computational Exercises
Thought Exercises
Projects and Challenges
References
Quantum Computing
Introduction
Motivation
Basic Concepts from Quantum Theory
From Classical to Quantum Mechanics
Wave-Particle Duality
Double-Slit with Bullets
Double-Slit with Water Waves
Double-Slit with Electrons
The Uncertainty Principle
Some Remarks
Principles from Quantum Mechanics
Dirac Notation
Quantum Superposition
Tensor Products
Entanglement
Evolution (Dynamics)
Measurement
No-Cloning Theorem
Quantum Information
Bits and Quantum Bits (Qubits)
Multiple Bits and Qubits
Gates and Quantum Gates
Generalizations of the Hadamard Gate
Quantum Circuits
Quantum Parallelism
Examples of Applications
Dense Coding
Quantum Teleportation
Universal Quantum Computers
Benioff's Computer
Feynman's Computer
Deutsch's Computer
Quantum Algorithms
Deutsch-Jozsa Algorithm
Simon's Algorithm
Shor's Algorithm
Quantum Fourier Transform
Factorization
Grover's Algorithm
Physical Realizations of Quantum Computers: A Brief Description
Ion Traps
Cavity Quantum Electrodynamics (CQED)
Nuclear Magnetic Resonance (NMR)
Quantum Dots
Scope of Quantum Computing
From Classical to Quantum Computing
Summary and Discussion
Exercises
Questions
Exercises
Thought Exercises
Projects and Challenges
References
Afterwords
New Prospects
The Growth of Natural Computing
Some Lessons from Natural Computing
Artificial Intelligence and Natural Computing
The Birth of Artificial Intelligence
The Divorce Between AI and CI
Natural Computing and the Other Nomenclatures
Visions
References
Appendix A
Glossary of Terms
Appendix B
Theoretical Background
Linear Algebra
Sets and Set Operations
Sets
Set Operations
Vectors and Vector Spaces
Scalar
Vector
Linear Vector Space
Linear Vector Subspace
Linear Variety
Convex Set
Linear Combinations, Spanning Sets, and Convex Combinations
Linear Dependence and Independence
Basis and Dimension of a Linear Vector Space
Dot (Inner) Product
Outer Product
Norms, Projections, and Orthogonality
Norms, Semi-Norms and Quasi-Norms
Orthogonal and Orthonormal Vectors
Projecting a Vector along a Given Direction
Orthonormal Vectors Generated from Linearly Independent Vectors
Matrices and Their Properties
Matrix
Basic Operations Involving Vectors and Matrices
Transpose and Square Matrices
Trace
Range and Rank
Symmetry
Inversion
Pseudo-inversion
Cofactor
Determinant
Adjoint
Singularity
Nullity
Eigenvalues and Eigenvectors
Positivity
Complex Numbers and Spaces
Complex Numbers
Complex Conjugate and Absolute Value
Complex Plane
Polar Coordinates
Exponential Form
Complex Matrices
Special Complex Matrices: Self-Adjoint (Hermitian), Unitary
Hilbert Spaces
Tensor Products
Statistics
Elementary Concepts
Population, Sample, Variables
Branches of Statistics
Probability
Event and Sample Space
Probability
Conditional Probability
Bayes Theorem
Counting
Discrete Random Variables
Random Variable
Discrete Random Variable
Probability Distributions
Summary and Association Measures
Central Tendency and Dispersion Measures
Association Measures
Estimation and Sample Sizes
Point and Interval Estimators
Confidence Interval
Theory of Computation and Complexity
Production Systems and Grammars
Universal Turing Machines
Complexity Theory
Other Concepts
Optimization
Logic of Propositions
Theory of Nonlinear Dynamical Systems
Graph Theory
Data Clustering
Affine Transformations
Fourier Transforms
Bibliography
Appendix C
A Quick Guide to the Literature
Introduction
Comments on Selected Bibliography
Main (General) Journals
Main Conferences
Conceptualization
Comments on Selected Bibliography
Evolutionary Computing
Comments on Selected Bibliography
Specific Journals
Specific Conferences
Neurocomputing
Comments on Selected Bibliography
Specific Journals
Specific Conferences
Swarm Intelligence
Comments on Selected Bibliography
Specific Journals
Specific Conferences
Immunocomputing
Comments on Selected Bibliography
Specific Journals
Specific Conferences
Fractal Geometry of Nature
Comments on Selected Bibliography
Specific Journals
Specific Conferences
Artifical Life
Comments on Selected Bibliography
Specific Journals
Specific Conferences
DNA Computing
Comments on Selected Bibliography
Specific Journals
Specific Conferences
Quantum Computing
Comments on Selected Bibliography
Specific Journals
Specific Conferences
Index

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