駆け足で読む『Bio-Inspired Artificial Intelligence』 目次

Bio-Inspired Artificial Intelligence: Theories, Methods, and Technologies (Intelligent Robotics and Autonomous Agents)

• 本の価値は、「本と言う１冊」が「何を」「どのくらいの分量で」「どういう順序、または構造で」所有するかだろう
• 情報化社会にあって、書いてある内容自体よりもその「取捨選択」と「構成・構造」の重要度が圧倒的に大きくなっており、その意味で「監修者」がまとめている場合は、その「監修者」が重要で、「一人筆者」の場合は「筆者の構成姿勢」が重要
• その点から、「大部」だけれど、よさそう。それは目次の構成を眺めるだけで全体像が見えることからもわかる
• 中身はこちら
• 大目次
  • 1. Evolutionary Systems 進化学の系
    • 情報を改変しつつ、(最)適化する仕組み
  • 2. Cellular Systems 細胞の系
    • 空間に自動機械があって、活動・発展・繰り返しする仕組み
  • 3. Neural Systems 神経学の系
    • 素子があって、相互作用のルールがあって、構造を作って、構造が機能を支える仕組み
  • 4. Developmental Systems 発生学の系
    • 単位構造から、限定的なルールのみを使って、複雑な構造を作りつつ、可塑性を持つ、集合体形成の仕組み
  • 5. Immune Systems 免疫学の系
    • 矛盾をはらんだ問題に対処する仕組み(あらゆる可能性への備え、敵味方の区別、強力と危険とは表裏一体)
  • 6. Behavioral Systems 行動学の系
    • 生命体と環境との相互のやりとりが繰り返されておきる仕組み
  • 7. Collective Systems 集合体の系
    • 個体が複数集まることで出現する仕組み
  • 8. Conclusion
• 細目次
  • 1. Evolutionary Systems
    • 1.1 Pillars of Evolutionary Theory
    • 1.2 The Genotype
    • 1.3 Artificial Evolution
    • 1.4 Genetic Representations
    • 1.5 Initial Population
    • 1.6 Fitness Functions
    • 1.7 Selection and Reproduction
    • 1.8 Genetic Operators
    • 1.9 Evolutionary Measures
    • 1.10 Types of Evolutionary Algorithms
    • 1.11 Schema Theory
    • 1.12 Human-Competitive Evolution
    • 1.13 Evolutionary Electronics
    • 1.14 Lessons from Evolutionary Electronics
    • 1.15 The Role of Abstraction
    • 1.16 Analog and Digital Circuits
    • 1.17 Extrinsic and Intrinsic Evolution
    • 1.18 Digital Design
    • 1.19 Evolutionary Digital Design
    • 1.20 Analog Design
    • 1.21 Evolutionary Analog Design
    • 1.22 Multiple Objectives and Constraints
    • 1.23 Design Verification
    • 1.24 Closing Remarks
    • 1.25 Suggested Readings
  • 2. Cellular Systems
    • 2.1 The Basic Ingredients
    • 2.2 Cellular Automata
    • 2.3 Modeling with Cellular Systems
    • 2.4 Some Classic Cellular Automata
    • 2.5 Other Cellular Systems
    • 2.6 Computation
    • 2.7 Artificial Life
    • 2.8 Complex Systems
    • 2.9 Analysis and Synthesis of Cellular Systems
    • 2.10 Closing Remarks
    • 2.11 Suggested Readings
  • 3. Neural Systems
    • 3.1 Biological Nervous Systems
    • 3.2 Artificial Neural Networks
    • 3.3 Neuron Models
    • 3.4 Architecture
    • 3.5 Signal Encoding
    • 3.6 Synaptic Plasticity
    • 3.7 Unsupervised Learning
    • 3.8 Supervised Learning
    • 3.9 Reinforcement Learning
    • 3.10 Evolution of Neural Networks
    • 3.11 Neural Hardware
    • 3.12 Hybrid Neural Systems
    • 3.13 Closing Remarks
    • 3.14 Suggested Readings
  • 4. Developmental Systems
    • 4.1 Potential Advantages of a Developmental Representation
    • 4.2 Rewriting Systems
    • 4.3 Synthesis of Developmental Systems
    • 4.4 Evolution and Development
    • 4.5 Defining Artificial Evolutionary Developmental Systems
    • 4.6 Evolutionary Rewriting Systems
    • 4.7 Evolutionary Developmental Programs
    • 4.8 Evolutionary Developmental Processes
    • 4.9 Closing Remarks
    • 4.10 Suggested Readings
  • 5. Immune Systems
    • 5.1 How Biological Immune Systems Work
    • 5.2 The Constituents of Biological Immune Systems
    • 5.3 Lessons for Artificial Immune Systems
    • 5.4 Algorithms and Applications
    • 5.5 Shape Space
    • 5.6 Negative Selection Algorithm
    • 5.7 Clonal Selection Algorithm
    • 5.8 Examples
    • 5.9 Closing Remarks
    • 5.10 Suggested Readings
  • 6. Behavioral Systems
    • 6.1 Behavior in Cognitive Science
    • 6.2 Behavior in Artificial Intelligence
    • 6.3 Behavior-Based Robotics
    • 6.4 Biological Inspiration for Robots
    • 6.5 Robots as Biological Models
    • 6.6 Robot Learning
    • 6.7 Evolution of Behavioral Systems
    • 6.8 Evolution and Learning in Behavioral Systems
    • 6.9 Evolution and Neural Development in Behavioral Systems
    • 6.10 Coevolution of Body and Control
    • 6.11 Toward Self-Reproduction
    • 6.12 Simulation and Reality
    • 6.13 Closing Remarks
    • 6.14 Suggested Readings
  • 7. Collective Systems
    • 7.1 Biological Self-Organization
    • 7.2 Particle Swarm Optimization
    • 7.3 Ant Colony Optimization
    • 7.4 Swarm Robots
    • 7.5 Coevolutionary Dynamics: Biological Models
    • 7.6 Artificial Evolution of Competing Systems
    • 7.7 Artificial Evolution of Cooperation
    • 7.8 Closing Remarks
    • 7.9 Suggested Readings
  • 8. Conclusion