Chapter 1 Why Deep Neural Networks: A Possible Theoretical Explanation

Chapter 2 Abstract Argumentation Frameworks to Promote Fairness and Rationality in Multi-experts Multi-criteria Decision Making

Chapter 3 Constraint Approach to Multi-objective Optimization

Chapter 4 From Global to Local Constraints: A Constructive Version of Bloch’s Principle

Chapter 5 Optimizing pred(25) Is NP-Hard

Chapter 6 Range Estimation Under Constraints Is Computable Unless There Is a Discontinuity

Chapter 7 Towards a Physically Meaningful Definition of Computable Discontinuous and Multi-valued Functions (Constraints)

Chapter 8 Algebraic Product is the only T-norm for Which Optimization Under Fuzzy Constraints is Scale-Invariant

Chapter 9 Comparing Operation Points in Linear Programming with Fuzzy Constraints

Chapter 10 On Modeling Multi-experts Multi-criteria Decision-Making Argumentation and Disagreement: Philosophical and Computational Approaches Reconsidered

Chapter 11 Positive Semidefiniteness and Positive Definiteness of a Linear Parametric Interval Matrix

Chapter 12 Automatic Loop-Shaping of $${H_\infty }$$ / $$\mu $$ Problem in QFT Using Interval Consistency Based Hybrid Optimization

Chapter 13 Existence of the Nash-Optimal Strategies in the Meta-Game

Chapter 14 Peak-End Rule: A Utility-Based Explanation

Chapter 15 Similarity Approach to Defining Basic Level of Concepts Explained from the Utility Viewpoint

Chapter 16 Comparisons of Measurement Results as Constraints on Accuracies of Measuring Instruments: When can we Determine the Accuracies from These Constraints?