Decision Making under Constraints (Studies in Systems, Decision and Control, 276)

✍ Scribed by Martine Ceberio (editor), Vladik Kreinovich (editor)

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 222
• Category: Library

✦ Synopsis

This book presents extended versions of selected papers from the annual International Workshops on Constraint Programming and Decision Making from 2016 to 2018. The papers address all stages of decision-making under constraints: (1) precisely formulating the problem of multi-criteria decision-making; (2) determining when the corresponding decision problem is algorithmically solvable; (3) finding the corresponding algorithms and making these algorithms as efficient as possible; and (4) taking into account interval, probabilistic, and fuzzy uncertainty inherent in the corresponding decision-making problems. In many application areas, it is necessary to make effective decisions under constraints, and there are several area-specific techniques for such decision problems. However, because they are area-specific, it is not easy to apply these techniques in other application areas. As such, the annual International Workshops on Constraint Programming and Decision Making focus on cross-fertilization between different areas, attracting researchers and practitioners from around the globe. The book includes numerous papers describing applications, in particular, applications to engineering, such as control of unmanned aerial vehicles, and vehicle protection against improvised explosion devices.

✦ Table of Contents

Preface
References
Contents
Fuzzy Systems Are Universal Approximators for Random Dependencies: A Simplified Proof
1 Formulation of the Problem
2 Towards a Simplified Proof
References
How Quantum Computing Can Help with (Continuous) Optimization
1 Formulation of the Problem
2 How This Optimization Problem Is Solved Now
3 How Quantum Computing Can Help
References
How Neural Networks (NN) Can (Hopefully) Learn Faster by Taking into Account Known Constraints
1 Formulation of the Problem
2 Neural Networks: A Brief Reminder
3 How to Pre-Train a NN to Satisfies Given Constraints
4 How to Retain Constraints When Training Neural Networks on Real Data
References
Fuzzy Primeness in Quantales
1 Introduction
2 Basic Definitions
3 Strong Primeness in Quantales
4 Fuzzy Prime and Fuzzy usp Ideals in Quantales
5 Final Remarks
References
A Short Introduction to Collective Defense in Weighted Abstract Argumentation Problems
1 Introduction and Preliminaries
2 Weighted Abstract AFs
3 Implementation
4 Related Work and Comparison
5 Conclusions and Future Work
References
Modeling and Specification of Nondeterministic Fuzzy Discrete-Event Systems
1 Introduction
2 Fuzzy Discrete-Event Systems
3 Nondeterministic Fuzzy Discrete-Event Systems
4 Bisimulation
5 Nondeterministic Fuzzy Specification
6 Conclusion and Future Work
References
Italian Folk Multiplication Algorithm Is Indeed Better: It Is More Parallelizable
1 Formulation of the Problem
2 Italian Algorithm Is Better: An Explanation
References
Reverse Mathematics Is Computable for Interval Computations
1 Formulation of the Problem
2 Definitions and the Main Result
3 Proof
References
Generalized Ordinal Sum Constructions of t-norms on Bounded Lattices
1 Introduction
2 Preliminaries
3 Generalized Ordinal Sum of Bounded Lattices
4 Interior Operator Based Ordinal Sum of T-Norms
5 Conclusion
References
A Comparison of Some t-Norms and t-Conorms over the Steady State of a Fuzzy Markov Chain
1 Introduction
2 Fuzzy Markov Chains
2.1 Ergodicity in FMs
2.2 Selected t-Norms and t-Conorms
3 An Example
3.1 Stationary Transition Matrices
3.2 Scalarization of P
3.3 Analysis of the Results
4 Concluding Remarks
References
Plans Are Worthless but Planning Is Everything: A Theoretical Explanation of Eisenhower's Observation
1 Introduction: Eisenhower's Seemingly Paradoxical Observation
2 Analysis of the Problem
3 Conclusions
References
Why Convex Optimization Is Ubiquitous and Why Pessimism Is Widely Spread
1 Why Convex Optimization Is Ubiquitous
2 Why Pessimism Is Widely Spread
References
Probabilistic Fuzzy Neural Networks and Interval Arithmetic Techniques for Forecasting Equities
1 Mathematical Stochastics
1.1 Brownian Motion
1.2 Ito;s Stochastic Differential and Ito's Lemma
2 Black-Scholes-Merton Model
3 The Underlying Price
4 Dupire Formula
5 Dynamic Optimization
5.1 Principle of Optimality and Stochastic Optimal Control
6 Fuzzification
7 Interval Fuzzy Modeling Algorithm for Optimal Forecast
8 Conclusion
References
P-Completeness of Testing Solutions of Parametric Interval Linear Systems
1 Introduction
2 Results
3 Conclusion
References
Thick Separators
1 Thick Sets
2 Thick Separators
3 Algebra
4 Using Karnaugh Map
5 Test Case
References
Using Constraint Propagation for Cooperative UAV Localization from Vision and Ranging
1 Introduction
2 Vision-Based Pose Computation
3 Using Range Measurements for Cooperative Localization
4 Experimental Results
5 Conclusion
References
Attraction-Repulsion Forces Between Biological Cells: A Theoretical Explanation of Empirical Formulas
1 Formulation of the Problem
2 Analysis of the Problem
3 Definitions and the Main Result
4 Proofs
References
When We Know the Number of Local Maxima, Then We Can Compute All of Them
1 Locating Local Maxima: An Important Practical Problem
2 What Is Computable: Reminder
3 Main Results
4 Proof of Proposition 1
5 Proof of Proposition 2
References
Why Decimal System and Binary System Are the Most Widely Used: A Possible Explanation
1 Formulation of the Problem
2 Analysis of the Problem
3 Code
Reference
Uncertainty in Boundary Conditions—An Interval Finite Element Approach
1 Introduction
2 Formulation
3 Example Problems
3.1 Example 1: Planar Truss with Uncertainty in Boundary Condition
3.2 Example 2: Planar Frame with Uncertainty in Boundary Condition
3.3 Example 3: Planar Frame with Uncertainty in Joint Rigidity
4 Conclusion
References
Which Value widetildex Best Represents a Sample x1,…,xn: Utility-Based Approach Under Interval Uncertainty
1 Which Value widetildex Best Represents a Sample x1,…,xn: Case of Exact Estimates
2 Case of Interval Uncertainty: Formulation of the Problem
3 Analysis of the Problem
4 Resulting Algorithm
References
Why Unexpectedly Positive Experiences Make Decision Makers More Optimistic: An Explanation
1 Formulation of the Problem
2 Formulating the Problem in Precise Terms
3 Towards the Desired Explanation
References
Back to Classics: Controlling Smart Thermostats with Natural Language… with Personalization
1 Introduction
2 Talking to a Smart Device…
3 Energy-Aware Temperature Adjustment Request
3.1 Example 1: “Increase the Temperature by Several Degrees”
3.2 Example 2: “I Am Cold”
4 Conclusion
References
The Role of Affine Arithmetic in Robust Optimal Power Flow Analysis
1 Motivations
1.1 Sampling Methods
1.2 Analytical Methods
1.3 Approximate Methods
1.4 Non-probabilistic Methods
1.5 Affine Arithmetic-Based Methods
2 Chapter Contributions
References
Balancing Waste Water Treatment Plant Load Using Branch and Bound
1 Introduction
2 Model Formulation
3 General Problem to Be Solved for Known Inflow
4 Typical Input Data
5 A Simple Greedy Algorithm
5.1 A Sketch of a Greedy Algorithm with Interval Arithmetic
6 Checks for the Feasibility of Constraints
6.1 A Simpler Problem
6.2 Infeasible Problems Due to Pumping Station Grouping
7 Conclusion
References
Why Burgers Equation: Symmetry-Based Approach
1 Formulation of the Problem
2 Let Us Use Symmetries
3 What Are the Symmetries of the Burgers' Equation
4 Burgers' Equation Can Be Uniquely Determined by Its Symmetries
References
Working on One Part at a Time Is the Best Strategy for Software Production: A Proof
1 Formulation of the Problem
2 Main Result
3 Proof
Reference