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