دانلود کتاب Towards Explainable Fuzzy AI: Concepts, Paradigms, Tools, and Techniques

فهرست مطالب :

Preface Contents 1 Why Explainable AI? Why Fuzzy Explainable AI? What Is Fuzzy? 1.1 Why Explainable AI? 1.2 Why Fuzzy Techniques Seem a Reasonable Approach for Explainable AI 1.3 What Is Fuzzy Methodology 1.4 Summary of Fuzzy Methodology 1.5 Exercises 2 Defuzzification 2.1 Formulation of the Problem: Reminder 2.2 Main Idea and the Resulting Formula 2.3 Integral Form 2.4 Important Comment: Centroid Defuzzification Is Not a Panacea 2.5 Exercises 2.6 Self-Test 1 3 Which Fuzzy Techniques? 3.1 What We Study in This Chapter 3.2 Interpolation Should Be Robust 3.3 Which Interpolation Is the Most Robust 3.4 ``And''- and ``Or''-Operations Must Be Robust Too 3.5 Which Is the Most Robust ``And''-Operation 3.6 Which Is the Most Robust ``Or''-Operation 3.7 Group Robustness Versus Individual Robustness 3.8 Which Interpolation Is the Most Individually Robust 3.9 The Most Individually Robust ``And''-Operation 3.10 Robustness Versus Individual Robustness: Example 3.11 The Most Individually Robust ``Or''-Operation 3.12 General Conclusion 3.13 Exercises 4 So How Can We Design Explainable Fuzzy AI: Ideas 4.1 Machine Learning Revisited 4.2 Exercises 4.3 Self-Test 2 5 How to Make Machine Learning Itself More Explainable 5.1 How Can We Make Machine Learning Itself More Explainable: Idea 5.2 Selection of an Activation Function 5.3 Selection of Pooling 5.4 What About Fuzzy? 5.5 Exercises 5.6 Self-Test 3 6 Final Self-Test Appendix A Terms Used in the Book (in Alphabetic Order) Appendix B Why Do We Need …? (in Alphabetic Order) Appendix C Solutions to Exercises Appendix D Solutions to Self-Tests D.1 Solutions to Self-Test 1 D.2 Solutions to Self-Test 2 D.3 Solutions to Self-Test 3 D.4 Solutions to Final Self-Test Appendix E Additional Readings