Abstract: Part 1. Soft Computing and Fuzzy Logic -- 1. Lotfi A. Zadeh’s Life and His Scientific Legacy -- 2. From Fuzzy Optimization to Possibilistic-Probabilistic Optimization with our Teacher Professor Lotfi Zadeh -- 3. Ideas of Lotfi Zadeh in Explainable Artificial Intelligence -- 4. Different Concepts, Similar Computational Complexity: Nguyen’s Results about Fuzzy and Interval Computations 35 Years. .

Abstract: This book is a collection of papers presented during the 8th World Conference on Soft Computing in February 2022. The papers cover multiple areas important for soft computing. Some papers are dedicated to fundamental aspects of soft computing, i.e., fuzzy mathematics, type-2 fuzzy sets, evolutionary-based optimization, aggregation, and neural networks. Others emphasize the application of soft computing methods to data analysis, image processing, decision-making, classification, series prediction, economics, control, and modeling.

Abstract: This book focuses on the use of artificial intelligence (AI) and computational intelligence (CI) in medical and related applications. Applications include all aspects of medicine: from diagnostics (including analysis of medical images and medical data) to therapeutics (including drug design and radiotherapy) to epidemic- and pandemic-related public health policies. Corresponding techniques include machine learning (especially deep learning), techniques for processing expert knowledge (e.g., fuzzy techniques), and advanced techniques of applied mathematics (such as innovative probabilistic and graph-based techniques). The book also shows that these techniques can be used in many other applications areas, such as finance, transportation, physics. This book helps practitioners and researchers to learn more about AI and CI methods and their biomedical (and related) applications—and to further develop this important research direction.

Abstract: Part 1. Fuzzy Recognition -- 01. Difficulties in recognizing flat shapes based on Fuzzy logic -- 2. The problem of parsing and recognizing individual objects of information on base of fuzzy Logic -- 3. Call Center and Robot Call Center How to Reduce the Cost -- 4. An intelligent method for optimizing calculations in the recognition of sound information.

Abstract: This book is a collection of papers presented during the 8th World Conference on Soft Computing in February 2022. The papers cover multiple areas important for soft computing. Some papers are dedicated to fundamental aspects of soft computing, i.e., fuzzy mathematics, type-2 fuzzy sets, evolutionary-based optimization, aggregation, and neural networks. Others emphasize the application of soft computing methods to data analysis, image processing, decision-making, classification, series prediction, economics, control, and modeling.

Abstract: Forcing the Network to use Human Explanations in its Inference Process -- Fuzzy Inference System-based Collision Avoidance of Unmanned Aerial Vehicles Optimized using Genetic Algorithm -- Fuzzy Logic-aided Inverse Kinematics Control for Redundant Manipulators -- Growth Kinetics of Gold Nanoparticles via p-fuzzy systems -- Optimization of Artificial Potential Field using Genetic Algorithm for Human-aware Navigation of Autonomous Mobile Robots -- Genetic Fuzzy Threat Assessment for Asteroids 2600 Derived Game -- Deep Learning ANFIS Architectures -- A Fuzzy Inference System for an Optimal Spacecraft Attitude State Trajectory -- Faster Algorithms for Estimating the Mean of a Quadratic Expression under Uncertainty -- People Prefer More Information About Uncertainty, But Perform Worse When Given This Information: An Explanation of the Paradoxical Phenomenon.

Abstract: This book is an overview of latest successes and applications of fuzzy techniques—techniques that use expert knowledge formulated by natural-language words like "small". Engineering applications deal with aerospace (control of spacecrafts and unmanned aerial vehicles, air traffic control, airport passenger flow predictions), materials (designing gold nano-structures for medicine, catalysis, and sensors), and robot navigation and manipulation. Other application areas include cosmology, demographics, finances, wine production, medicine (diagnostics, epidemics control), and predicting human behavior. In many cases, fuzzy techniques are combined with machine learning AI. Due to natural-language origin of fuzzy techniques, such combination adds explainability (X) to AI. This book is recommended to students and practitioners interested in the state-of-the-art fuzzy-related XAI and to researchers willing to take on numerous remaining challenges.

Abstract: Preface -- directory Preface -- 1. Applications to Biology and Medicine -- Hunting Habits of Predatory Birds: Theoretical Explanation of an Empirical Formula -- Why Rectified Power (RePU) Activation Functions Are Efficient in Deep Learning: A Theoretical Explanation -- Aquatic Ecotoxicology: Theoretical Explanation of Empirical Formulas -- How Hot Is Too Hot -- How Order and Disorder Affect People's Behavior: An Explanation -- Shape of an Egg: Towards a Natural Simple Universal Formula -- A General Commonsense Explanation of Several Medical Results -- Why Immunodepressive Drugs Often Make People Happier -- Systems Approach Explains Why Low Heart Rate Variability Is Correlated with Depression (and Suicidal Thoughts) -- 2. Applications to Economics and Politics -- How to Make Inflation Optimal and Fair -- Why Seneca Effect? -- Why Rarity Score Is a Good Evaluation of a Non-Fungible Token -- Resource Allocation for Multi-Tasking Optimization: Explanation of an Empirical Formula -- Everyone Is Above Average: Is It Possible? Is It Good? -- How Probable is a Revolution? A Natural ReLU-Like Formula that Fits the Historical Data -- Why Should Exactly 1/4 Be Returned to the Original Owner: An Economic Explanation of an Ancient Recommendation -- Why Would Anyone Invest in a High-Risk Low-Profit Enterprise? -- Which Interval-Valued Alternatives Are Possibly Optimal If We Use Hurwicz Criterion -- How to Solve the Apportionment Paradox -- In the Absence of Information, the Only Reasonable Negotiation Scheme Is Offering a Certain Percentage of the Original Request: A Proof -- 3. Applications to Education -- How to Make Quantum Ideas Less Counter-Intuitive: A Simple Analysis of Measurement Uncertainty Can Help -- Physical Meaning Often Leads to Natural Derivations in Elementary Mathematics: On the Examples of Solving Quadratic and Cubic Equations -- Towards Better Ways to Compute the Overall Grade for a Class -- Why Some Theoretically Possible Representations of Natural Numbers Were Historically Used and Some Were Not: An Algorithm-Based Explanation -- 4. Applications to Engineering -- Dielectric Barrier Discharge (DBD) Thrusters -- Aerospace Engines of the Future: Invariance-Based Analysis -- Need for Optimal Distributed Measurement of Cumulative Quantities Explains the Ubiquity of Absolute and Relative Error Components -- Over-Measurement Paradox: Suspension of Thermonuclear Research Center and Need to Update Standards -- How to Get the Most Accurate Measurement-Based Estimates -- How to Estimate The Present Serviceability Rating of a Road Segment: Explanation of an Empirical Formula -- 5. Applications to Linguistics -- Word Representation: Theoretical Explanation of an Empirical Fact -- Why Menzerath's Law? -- 6. Applications to Machine Learning -- One More Physics-Based Explanation for Rectified Linear Neurons -- Why Deep Neural Networks: Yet Another Explanation -- 7. Applications to Mathematics -- Really Good Theorems Are Those That End Their Life as Definitions: Why -- 8. Applications to Physics -- How to Describe Hypothetic Truly Rare Events (with Probability 0) -- Spiral Arms Around a Star: Geometric Explanation -- Why Physical Power Laws Usually Have Rational Exponents -- Freedom of Will, Non-Uniqueness of Cauchy Problem, Fractal Processes, Renormalization, Phase Transitions, and Stealth Aircraft -- How Can the Opposite to a True Theory Be Also True? A Similar Talmudic Discussion Helps Make This Famous Bohr's Statement Logically Consistent -- How to Detect (and Analyze) Independent Subsystems of a Black-Box (or Grey-Box) System -- 9. Applications to Psychology and Decision Making -- Why Decision Paralysis -- Why Time Seems to Pass Slowly for Unpleasant Experiences and Quickly for Pleasant Experiences: An Explanation Based on Decision Theory -- How to Deal with Conflict of Interest Situations When Selecting the Best Submission -- Why Aspirational Goals: Geometric Explanation -- Why Hate: Analysis Based on Decision Theory -- Why Self-Esteem Helps to Solve Problems: An Algorithmic Explanation -- Why Five Stages of Solar Activity, Why Five Stages of Grief, Why Seven Plus Minus Two: A General Geometric Explanation -- 10. Applications to Software Engineering -- Anomaly Detection in Crowdsourcing: Why Midpoints in Interval-Valued Approach -- Unexpected Economic Consequence of Cloud Computing: A Boost to Algorithmic Creativity -- Unreachable Statements Are Inevitable In Software Testing: Theoretical Explanation -- 11. General Computational Techniques -- Why Constraint Interval Arithmetic Techniques Work Well: A Theorem Explains Empirical Success" -- "How to Describe Relative Approximation Error? A New Justification for Gustafson's Logarithmic Expression" -- Search Under Uncertainty Should be Randomized: A Lesson From the 2021 Nobel Prize in Medicine" -- Why Convex Combination Is an Effective Crossover Operation in Continuous Optimization: A Theoretical Explanation" -- "Why Optimization Is Faster than Solving Systems of Equations: A Qualitative Explanation" -- Estimating Skewness and Higher Central Moments of an Interval-Valued -- Fuzzy Set" -- How to Detect the Fundamental Frequency: Approach Motivated by Soft -- Computing and Computational Complexity" -- What If There Are Too Many Outliers?" -- What Is a Natural Probability Distribution on the Class of All Continuous Functions: Maximum Entropy Approach Leads to Wiener Measure" -- An Argument in Favor of Piecewise-Constant Membership Functions" -- "Data Processing under Fuzzy Uncertainty: Towards More Accurate Algorithms" -- "Epistemic vs. Aleatory: Case of Interval Uncertainty" -- "Standard Interval Computation Algorithm Is Not Inclusion-Monotonic: Examples" -- "Monotonic Bit-Invariant Permutation-Invariant Metrics on the Set of All Infinite Binary Sequences" -- Computing the Range of a Function-of-Few-Linear-Combinations Under Linear Constraints: A Feasible Algorithm" -- "How to Select a Representative Sample for a Family of Functions?.

Abstract: In the first approximation, decision making is nothing else but an optimization problem: We want to select the best alternative. This description, however, is not fully accurate: it implicitly assumes that we know the exact consequences of each decision, and that, once we have selected a decision, no constraints prevent us from implementing it. In reality, we usually know the consequences with some uncertainty, and there are also numerous constraints that needs to be taken into account. The presence of uncertainty and constraints makes decision making challenging. To resolve these challenges, we need to go beyond simple optimization, we also need to get a good understanding of how the corresponding systems and objects operate, a good understanding of why we observe what we observe – this will help us better predict what will be the consequences of different decisions. All these problems – in relation to different application areas – are the main focus of this book.

Abstract: Method for the Computation of the Interval Hull to Solutions of Interval and Fuzzy Interval Linear Systems -- Fuzzy-Petri-Networks in Supervisory Control of Markov Processes in Robotized FMS and Robotic Systems -- Using Fuzzy Set Approaches for Linguistic Data Summaries -- Fuzzy or Neural, Type-1 or Type-2 – When Each Is Better: First-Approximation Analysis.

Abstract: This book presents an authoritative collection of contributions reporting on computational intelligence, fuzzy systems as well as artificial intelligence techniques for modeling, optimization, control and decision-making together with applications and case studies in engineering, management and economic sciences. Dedicated to the Academician of the Polish Academy of Sciences, Professor Janusz Kacprzyk in recognition of his pioneering work, the book reports on theories, methods and new challenges in artificial intelligence, thus offering not only a timely reference guide but also a source of new ideas and inspirations for graduate students and researchers alike. The book consists of the 18 chapters, presented by distinguished and experienced authors from 16 different countries (Australia, Brazil, Canada, Chile, Germany, Hungary, Israel, Italy, China, R.N.Macedonia, Saudi Arabia, Spain, Turkey, United States, Ukraine, and Vietnam). All chapters are grouped into three parts: Computational Intelligence and Fuzzy Systems, Artificial Intelligence Techniques in Modelling and Optimization, and Computational Intelligence in Control and Decision Support Processes. The book reflects recent developments and new directions in artificial intelligence, including computation method of the interval hull to solutions of interval and fuzzy interval linear systems, fuzzy-Petri-networks in supervisory control of Markov processes in robotic systems, fuzzy approaches for linguistic data summaries, first-approximation analysis for choosing fuzzy or neural systems and type-1 or type-2 fuzzy sets, matrix resolving functions in game dynamic problems, evolving stacking neuro-fuzzy probabilistic networks and their combined learning in online pattern recognition tasks, structural optimization of fuzzy control and decision-making systems, neural and granular fuzzy adaptive modeling, state and action abstraction for search and reinforcement learning algorithms. Among the most successful and perspective implementations in practical areas of human activity are tentative algorithms for neurological disorders, human-centric question-answering system, OWA operators in pensions, evaluation of the perception of public safety through fuzzy and multi-criteria approach, a multicriteria hierarchical approach to investment location choice, intelligent traffic signal control and generative adversarial networks in cybersecurity.