駆け足で読む『Bio-Inspired Artificial Intelligence』の中身　5. 免疫学の系

5. Immune Systems
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)
- 病原体とホスト
- 免疫系
- 人工的免疫系
- 5.1 How Biological Immune Systems Work
  - 5.1.1 The Innate Immune System 先天免疫系
    - Pattern recognition receptors (PARs)
    - Antigen 抗原
    - Autoantigen 自己抗原
    - Pathogen-associated molecular patterns (PAMPs)
  - 5.1.2 The Limits of Innate Immunity
  - 5.1.3 Monitorin of Subsystems 免疫担当細胞が直接入り込めない部分(Subsystems)を監視する
  - 5.1.4 The Adaptive Immune System 獲得免疫系
    - Negative selection, positive selection
    - Danger signal
    - Central, peripheral torelance 免疫寛容
    - Antigen presenting cells (APCs)
    - Costimulation
    - Immunological synapse 免疫担当細胞の直接接触性コミュニケーション
    - Somatic hypermutation, affinity maturation, immune memory
  - 5.1.5 The Limits of Adaptive Immunity
    - Primary, secondary response
    - Autoimmune diseases
- 5.2 The Constituents of Biological Immune Systems 生物の免疫系の構成要素
  - Analog and digital recognition
  - Cellular and humoral immunity
  - Phagocytes
  - Commplement systems
  - Dendritic cells
  - Lymphatic system
  - MHC class II
  - Natural killer cell
  - T cell, Th, Tc, Tc antigen receptors
  - Gene libraries
  - Monospecificity of T
  - MHC restriction
  - B cell
  - Antibody, antigen-binding region, B cell antigen receptors
  - Somatic hypermutation
- 5.3 Lessons for Artificial Immune Systems
  - Performance
  - Costs
  - Dagame and Regeneration
  - Design for Immunity
  - Distributedness, Decentralization, Self-Protection, Robustness
  - Parallel Operation and Scalability
  - Adaptibity, Tolerance, Autoimmunity
  - Dynamic Allocation of Resources and Self-Limitation
  - Circulation of Detectors and Effectors
  - Adaptation of Local Sensityivity
  - Generation of Diversity
  - Strategies of Detection
  - Choice of Effector
  - Learning and Memory
  - Population Diversity
- 5.4 Algorithms and Applications
  - Danger model, traditional model, sele/nonself discrimination, immune network model
- 5.5 Shape Space 抗原の空間認識
  - 5.5.1 Example: Vaccine Design
- 5.6 Negative Selection Algorithm
- 5.7 Clonal Selection Algorithm
- 5.8 Examples
  - 5.8.1 ARTIS and LISYS Artificial immune system, Lightweight intrusion detection system
- 5.9 Closing Remarks
- 5.10 Suggested Readings