Artificial Intelligence in Control and Decision-making Systems: Dedicated to Professor Janusz Kacprzyk

Academician Professor Janusz Kacprzyk
Contents
Introduction
Computational Intelligence and Fuzzy Systems
Methods for the Computation of the Interval Hull to Solutions of Interval and Fuzzy Interval Linear Systems
1 Introduction
2 Four Cases
2.1 Case 1
2.2 Case 2
2.3 Case 3
2.4 Case 4
3 The Pivkina/Kreinovich Algorithm
4 Fuzzy Linear Systems
4.1 Example
4.2 General Fuzzy System Case for Triangular and Trapezoidal Fuzzy Interval Coefficients
5 Conclusions
References
Fuzzy-Petri-Networks in Supervisory Control of Markov Processes in Robotized FMS and Robotic Systems
1 Introduction
2 Plant Objects and Processes of Control as Controlled General Systems
3 Generalized and IPDI Complex Networks and Systems: Control, Decision and Management
4 Emulation Simulation of Robotized FMS and Robotic Systems
5 Cao and Sanderson’s Fuzzy-Petri-Nets for Task-Sequences in FMS and Robotic Systems
6 An Overview of the Background Research and Development Explorations
7 Higher Level of Decision and Control: Forecasting, Control and Supervision
7.1 Fuzzy Regression Based Forecasting and Control Expert Support System
7.2 Markov Chain Model State Estimation Via the Fuzzy-Petri-Net Reasoning Supervisor
8 Concluding Summary
References
Using Fuzzy Set Approaches for Linguistic Data Summaries
1 Introduction
2 Linguistic Summaries Basics
2.1 Validation of Linguistic Summaries
2.2 Natural Language Linguistic Quantifiers
2.3 Examples
2.4 Multi-attribute Linguistic Summaries
3 Information Measures of Summaries with Linguistic Content
3.1 Informativeness of Linguistic Summaries
3.2 Linguistic Summaries and Specificity
3.3 Informativeness of Summaries with Association Rules
4 Concepts and Hierarchies
4.1 Rich Concepts
4.2 Aggregation of Concepts
4.3 Hierarchical Framework for Rich Concepts
5 Composing Concepts Using the OWA Operator
5.1 OWA Weights Using Linguistic Quantifiers
5.2 OWA Concept Modules
References
Fuzzy or Neural, Type-1 or Type-2—When Each Is Better: First-Approximation Analysis
1 Formulation of the Problem
2 Analysis of the Problem
3 First-Approximation Model and the Resulting Recommendation
4 Future Work
References
Matrix Resolving Functions in Game Dynamic Problems
1 Introduction
2 Problem Statement. Strategies of the Player Behavior
3 The Pontryagin Condition. Method Scheme
4 Sufficient Conditions for the Game Termination
5 Counter-Controls in the Game Problem of Approach
6 Method Scheme with Fixed Selections of the Solid Part of the Terminal Set
7 Conclusion
References
Evolving Stacking Neuro-Fuzzy Probabilistic Networks and Their Combined Learning in Online Pattern Recognition Tasks
1 Introduction
2 Neuro-Fuzzy-Probabilistic Network
2.1 Architecture of Neuro-Fuzzy-Probabilistic Network
2.2 Evolving of NFPN in the Layer of Patterns
2.3 Results of Experiment
3 Probabilistic Neuro-Fuzzy System with One Dimensional Membership Function
4 Matrix Fuzzy-Probabilistic Neural Network in Image Recognition Task
5 Fast Image Recognition Using Double Hyper Basis Function Neural Network and Its Combined Learning
6 Conclusion
References
Artificial Intelligence Techniques in Modelling and Optimization
Intelligent Information Technology for Structural Optimization of Fuzzy Control and Decision-Making Systems
1 Introduction
2 Problem Statement and Related Works
3 Intelligent Information Technology for Finding Optimal Membership Functions of FSs Based on Bioinspired Evolutionary Algorithms
4 Bioinspired Evolutionary Optimization Algorithms Adapted to Solve the Problem of Finding the Optimal LTMFs of the FS
5 Search for Optimal Membership Functions for the Fuzzy ACS of the Multi-purpose Mobile Robot
6 Conclusions
References
Neural and Granular Fuzzy Adaptive Modeling
1 Introduction
2 Adaptive Neuro-Fuzzy and Granular Min-Max Modeling
2.1 Uninorm-Based Evolving Neural Network Modeling
2.2 Granular Evolving Min-Max Modeling
3 Results
3.1 Box and Jenkins Gas Furnace Identification
3.2 Mackey-Glass Time Series
4 Conclusion
References
State and Action Abstraction for Search and Reinforcement Learning Algorithms
1 Introduction
2 Preliminaries
2.1 Markov Decision Processes
2.2 Reinforcement Learning
2.3 Search/Optimization-Based Decision-Making
3 State Abstractions
3.1 Bisimulation Approaches
3.2 State Aggregation Approaches
3.3 Representation Discovery Approaches
3.4 Graph Compression Using High-Level Knowledge
4 Action Abstractions
4.1 Script-Based Action Abstraction
4.2 Portfolio-Based Search Algorithms
4.3 Constructing Higher Level Actions
5 Conclusion and Future Directions
References
A Tentative Algorithm for Neurological Disorders
1 Presentation
2 Basic Aspects for the Diagnosis of PD
3 Establishment of Sets of Incident and Incidental Elements
4 The Opinion of the Experts
5 Technical Elements that Precede the Development of the Algorithm
6 The Phases of the Algorithm
7 Development of the Algorithm Based on Previous Information from Experts
8 Analysis of Forgotten Incidences
9 Intermediation Role of Some Affected Neurons and Certain Symptoms of PD
10 Conclusions
References
On the Use of Quasi-Sigmoids in Function Approximation Problems with Neural Networks
1 Introduction
2 Static Backpropagation Algorithm in Function Approximation Problems
3 Considerations on the Learning Process in Multilayer NN
4 Sigmoidal Equivalent of a Quasi-Sigmoidal NN
5 A Gradient Descent Procedure on the Steepness Parameter of Quasi-Sigmoids
6 Quasi-Sigmoids and Gain Parameters in Standard Sigmoids
7 Experimental Results in Function Approximation Problems
8 Concluding Remarks
References
Human-Centric Question-Answering System with Linguistic Terms
1 Introduction
2 Question-Answering System LingTeQA: Overview
3 Question Representation
3.1 Phrasal Dependency Tree—Definition
3.2 Tree Generation
4 LingTeQA: Template Repository Construction
4.1 Question Template Generator
4.2 Query Template Generator
4.3 Mapping Natural Language Expressions into Knowledge Graph's Semantic Items
5 LingTeQA: Answering Questions
6 LingTeQA: Questions with Linguistic Terms
6.1 iPad System for Defining Linguistic Terms and Quantifiers
6.2 Web Interface for Defining Linguistic Terms
6.3 Function Fitting
6.4 Detecting Linguistic Terms in Questions
7 LingTeQA: Answering Questions with Linguistic Terms
8 Related Work
8.1 Construction of Fuzzy Sets
8.2 Fuzzy Queries and Relational Databases
9 Conclusion
References
Computational Intelligence in Control and Decision Support Processes
OWA Operators in Pensions
1 Introduction
2 Preliminaries
3 The Ordered Weighted Averaging Real Average Pension
3.1 The OWARAP Operator
3.2 The IOWARAP Operator
3.3 Generalized Aggregation Operators
4 Some Other Extensions of the OWARAP Operator
5 Real Average Pensions Forecasting with OWARAP Operators
5.1 Proposed Methodology
5.2 Illustrative Example
5.3 Comparison of Forecasting Methods
6 The COVID-19 Crisis on Pensions: Applicability of the OWA Operators
7 Conclusions
References
Evaluation of the Perception of Public Safety Through Fuzzy and Multi-criteria Approach
1 Introduction
2 Methodology
3 Results
3.1 Identification of the Criteria
3.2 Normalization of Variables
3.3 Determination of Weights Through Personal Construction Theory
3.4 Decision Matrix
3.5 Final Calculations and Orderings
4 Conclusions
References
A Multicriteria Hierarchical Approach to Investment Location Choice
1 Introduction
2 Theoretical Framework
3 Data Description
3.1 Financial Market Indicators
3.2 Economic Situation and Growth Indicators
3.3 Labor Market and Purchasing Power Indicators
3.4 Foreign Commercial Operations Indicator
3.5 Fiscal Indicators
4 The Multiple Criteria Hierarchy Process
5 Investment Location in Latin American Countries with an MCHP
5.1 Definition of Investment Location Choice as a Multiple Criteria Decision-Making Problem
5.2 Application of the Hierarchical ELECTRE III
6 Discussion
7 Conclusion
References
Uncertainty in Computer and Decision-Making Sciences: A Bibliometric Overview
1 Introduction
2 Methodology
3 Structured Results and Observations
4 Conclusions
References
Intelligent Traffic Signal Control Using Rule Based Fuzzy System
1 Introduction
2 Overview of the Related Work
3 The Basic Model, the Methodology and the Formal Tools in the Proposed Approach
3.1 The Distribution of Vehicle Arrivals
3.2 Computation of the Average Delay Time of the Vehicles
3.3 The Software Tools
3.4 The Case Study and the Fuzzy Model for the Proposed Novel Fuzzy Traffic Control System
4 A Simple Case Study of the Implementation of the Proposed Traffic Signal Control System
4.1 The Heavy Traffic Evaluation Module (HTEM)
4.2 The Prioritize Emergency Car Module (PECM)
4.3 Extension Time Decision Module (ETDM)
5 Simulation Analysis and Discussion
6 Conclusions and Future Work
References
Generative Adversarial Networks in Cybersecurity: Analysis and Response
1 Introduction
2 GAN Application Analysis in the Context of Cybersecurity
2.1 Malware
2.2 Password Guessing
2.3 Deepfakes and Image Manipulation
2.4 Forging Biometric Data
2.5 Steganography
2.6 Denial-of-Service Attacks
2.7 Intrusion and Botnet Detection
3 Response and Forensics
3.1 Incident Response Overview
3.2 Digital Forensics
4 Conclusions
References