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Flexible and generalized uncertainty optimization : theory and approaches / / Weldon A. Lodwick, Luiz L. Salles-Neto
| Flexible and generalized uncertainty optimization : theory and approaches / / Weldon A. Lodwick, Luiz L. Salles-Neto |
| Autore | Lodwick Weldon A. |
| Edizione | [Second edition.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (IX, 193 p. 34 illus., 30 illus. in color.) |
| Disciplina | 519.3 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Mathematical optimization
Uncertainty (Information theory) Fuzzy sets |
| ISBN | 3-030-61180-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | An Introduction to Generalized Uncertainty Optimization -- Generalized Uncertainty Theory: A Language for Information Deficiency -- The Construction of Flexible and Generalized Uncertainty Optimization Input Data -- An Overview of Flexible and Generalized Uncertainty Optimization -- Flexible Optimization -- Generalized Uncertainty Optimization -- References. . |
| Record Nr. | UNINA-9910484954903321 |
Lodwick Weldon A.
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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From intervals to -? : towards a general description of validated uncertainty / / Vladik Kreinovich, Graçaliz Pereira Dimuro, Antônio Carlos da Rocha Costa
| From intervals to -? : towards a general description of validated uncertainty / / Vladik Kreinovich, Graçaliz Pereira Dimuro, Antônio Carlos da Rocha Costa |
| Autore | Kreinovich Vladik |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (125 pages) |
| Disciplina | 006.3 |
| Collana | Studies in computational intelligence |
| Soggetto topico |
Computational intelligence
Uncertainty (Information theory) |
| ISBN | 3-031-20569-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- 1 Motivation and Outline -- 1.1 Why Computers? -- 1.2 Why Interval Computations? -- 1.3 Why Go Beyond Intervals? -- 1.4 Outline -- References -- 2 A General Description of Measuring Devices: Plan -- 3 A General Description of Measuring Devices: First Step-Finite Set of Possible Outcomes -- 3.1 Every Measuring Device Has Finitely Many Possible Outcomes -- 3.2 Not All Marks on a Scale Can Be Physically Possible -- 3.3 We Need a Theory -- 3.4 We Need a Theory that Also Described a Measuring Device -- 3.5 We Want a Theory that Is ``Full'' in Some Natural Sense -- 3.6 A Seemingly Natural Definition of a Full Theory is Not Always Adequate -- 3.7 What Exactly Is a Theory? -- 3.8 What Kind of Statements Are We Allowing? -- 3.9 What Exactly Is a Full Theory -- 3.10 The Existence of a Full Theory Makes the Set of All Physically … -- 3.11 Conclusion: Algorithmically Listable Set of Physically Possible Outcomes -- 3.12 Example 1: Interval Uncertainty -- 3.13 Example 2: Counting -- 3.14 Example 3: ``Yes''-``No'' Measurements -- 3.15 Example 3a: Repeated ``Yes''-``No'' Measurements -- 3.16 Example 4: A Combination of Several Independent Measuring Instruments -- References -- 4 A General Description of Measuring Devices: Second Step-Pairs of Compatible Outcomes -- 4.1 How Do We Describe Uncertainty: Main Idea -- 4.2 Comment on Quantum Measurements -- 4.3 Some Pairs of Outcomes Are Compatible (Close), Some Are Not -- 4.4 The Existence of a Full Theory Makes the Set of All Compatible Pairs of Outcomes Algorithmically Listable -- 4.5 Conclusion: Algorithmically Listable Set of Compatible Pairs of Outcomes -- 4.6 Description in Terms of Existing Mathematical Structures -- 4.7 Example 1: Interval Uncertainty -- 4.8 Example 2: Counting -- 4.9 Example 3: ``Yes''-``No'' Measurements.
4.10 Example 3a: Repeated ``Yes''-``No'' Measurements -- 4.11 Example 4: A Combination of Several Independent Measuring Instruments -- 4.12 Computational Complexity of the Graph Representation of a Measuring Device: General Case -- 4.13 Computational Complexity of the Graph Representation of a Measuring Device: Case of the Simplest Interval Uncertainty -- 4.14 Computational Complexity of the Graph Representation of a Measuring Device: General Case of Interval Uncertainty -- 4.15 Computational Complexity of the Graph Representation of a Measuring Device: Lower Bound for the Case of the General Interval Uncertainty -- 4.16 Computational complexity of the Graph Representation of a Measuring Device: Case of Multi-D Uncertainty -- 4.17 Computational Complexity of the Graph Representation of a Measuring Device: General Case of Localized Uncertainty -- References -- 5 A General Description of Measuring Devices: Third Step-Subsets of Compatible Outcomes -- 5.1 From Pairs to Subsets -- 5.2 Is Information About Compatible Pairs Sufficient? -- 5.3 Information About Compatible Pairs Is Sufficient For Intervals -- 5.4 Information About Compatible Pairs is Not Sufficient in the General Case -- 5.5 The Existence of a Full Theory Makes the Family of All Compatible … -- 5.6 Conclusion: Algorithmically Listable Family of Compatible Sets of Outcomes -- 5.7 Description in Terms of Existing Mathematical Structures: Simplicial Complexes -- 5.8 Resulting Geometric Representation of a Measuring Device -- 5.9 Towards Description in Terms of Existing Mathematical Structures: Domains -- 5.10 How to Reformulate the Above Description of a Measuring Device in Terms of Domains? -- 5.11 Example 1: Interval Uncertainty -- 5.12 Example 2: Counting -- 5.13 Example 3: ``Yes''-``No'' Measurements -- 5.14 Example 4: A Combination of Several Independent Measuring Instruments. 5.15 Computational Complexity of the Simplicial Complex Representation … -- 5.16 Computational Complexity of the Simplicial Complex Representation of a Measuring Device: Case of Interval Uncertainty -- 5.17 Computational Complexity of the Simplicial Complex Representation of a Measuring Device: Case of Multi-D Uncertainty -- 5.18 Computational Complexity of the Simplicial Complex Representation of a Measuring Device: General Case of Localized Uncertainty -- References -- 6 A General Description of Measuring Devices: Fourth Step-Conditional Statements About Possible Outcomes -- 6.1 Subsets of Compatible Outcomes Do Not Always Give A Complete Description of a Measuring Device -- 6.2 What We Do We Need to Add to the Subsets Description to Capture the Missing Information About a Measuring Device? -- 6.3 The Existence of a Full Theory Makes the Set of All True Conditional Statements Algorithmically Listable: An Argument -- 6.4 Family of Conditional Statements: Natural Properties -- 6.5 Conclusion: Algorithmically Listable Family of Conditional Statements -- 6.6 Description in Terms of Existing Mathematical Structures: Deduction Relation -- 6.7 Description in Terms of Existing Mathematical Structures: Domains -- 6.8 Example 1: Interval Uncertainty -- 6.9 Example 2: Counting -- 6.10 Example 3: ``Yes''-``No'' Measurements -- 6.11 Example 4: A Combination of Several Independent Measuring Instruments -- 6.12 Computational Complexity of the Domain Representation of a Measuring Device: A General Case -- 6.13 Computational Complexity of the Domain Representation of a Measuring Device: Case of Interval Uncertainty -- 6.14 Computational Complexity of the Simplicial Complex Representation of a Measuring Device: Case of Convex Multi-D Uncertainty. 6.15 Computational Complexity of the Domain Representation of a Measuring Device: General Case of Localized Uncertainty -- References -- 7 A General Description of Measuring Devices: Fifth Step-Disjunctive Conditional Statements About the Possible Outcomes -- 7.1 Addition of Conditional Statements Does Not Always Lead to a Complete Description of a Measuring Device -- 7.2 What We Do We Need to Add to the Conditional Statements Description to Capture the Missing Information About a Measuring Device? -- 7.3 The Existence of a Full Theory Makes the Set of All True Disjunctive Conditional Statements Algorithmically Listable -- 7.4 Family of True Disjunctive Conditional Statements: Natural Properties -- 7.5 Conclusion: Algorithmically Listable Family of Disjunctive Conditional Statements -- 7.6 Description in Terms of Existing Mathematical Structures: Sequent Calculus -- 7.7 Description in Terms of Existing Mathematical Structures: Boolean Vectors -- 7.8 Example -- 7.9 Description in Terms of Existing Mathematical Structures: Boolean Algebra -- 7.10 Example -- 7.11 Description in Terms of Existing Mathematical Structures: Domains -- 7.12 Example -- 7.13 Is This a Final Description of Validated Uncertainty? -- 7.14 Example 1: Interval Uncertainty -- 7.15 Example 2: Counting -- 7.16 Example 3: ``Yes''-``No'' Measurements -- 7.17 Example 4: A Combination of Several Independent Measuring Instruments -- 7.18 Computational Complexity of the Boolean Representation of a Measuring Device: A General Case -- 7.19 Computational Complexity of the Boolean Representation of a Measuring Device: Case of Interval Uncertainty -- 7.20 Computational Complexity of the Boolean Representation of a Measuring Device: Case of Convex Multi-D Uncertainty -- 7.21 Computational Complexity of the Domain Representation of a Measuring Device: General Case of Localized Uncertainty. References -- 8 A General Description of Measuring Devices: Summary -- 8.1 Summary -- 8.2 Measuring Device: A Final Description -- 9 Physical Quantities: A General Description -- 9.1 General Idea -- 9.2 From the General Idea to a Formal Description -- 9.3 Set of Possible Outcomes: The Notion of a Projection -- 9.4 Pairs of Compatible Outcomes: The Notion of a Projection -- 9.5 Subsets of Compatible Outcomes: The Notion of a Projection -- 9.6 Definition Reformulated in Domain Terms -- 9.7 General Domains and Boolean Vectors: The Notion of a Projection -- 9.8 The Family of All Measuring Devices Measuring A Given … -- 9.9 Physical Quantity as a Projective Limit of Measuring Devices -- 9.10 Example -- 9.11 Within This Definition, The Fact that Every Outcome … -- 9.12 Different Sequences of Measurement Results May Correspond to the Same Value of the Measured Quantity -- 9.13 Case of Graphs -- 9.14 Within This Definition, The Fact that simI Describes Exactly Compatible Pairs Is Now a Theorem -- 9.15 Case of Simplicial Complexes -- 9.16 Within This Definition, The Fact that calSI Describes Exactly Compatible Subsets Is Now A Theorem -- 9.17 Cases of Conditional Statements and Boolean Vectors -- 9.18 Examples: A Brief Introduction -- 9.18.1 Example 1: Interval Uncertainty Leads to Real Numbers -- 9.19 Conclusion -- 9.20 Example 2: Counting Leads to Natural Numbers -- 9.21 Example 3: ``Yes''-``No'' Measurements Lead to Truth Values -- 9.22 Example 4: A Combination of Several Independent Physical Quantities -- References -- 10 Properties of Physical Quantities -- 10.1 A Useful Auxiliary Result: We Can Always Restrict Ourselves to a Sequence of Measuring Devices -- 10.1.1 From the Physical Viewpoint, It is Important to Consider the Most General Families of Measuring Devices. 10.1.2 From the Purely Mathematical Viewpoint (of Proving Results), it is Desirable to Consider the Simpler Case of Sequences. |
| Record Nr. | UNINA-9910632469303321 |
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Kreinovich Vladik
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| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The geometry of uncertainty : the geometry of imprecise probabilities / / Fabio Cuzzolin
| The geometry of uncertainty : the geometry of imprecise probabilities / / Fabio Cuzzolin |
| Autore | Cuzzolin Fabio |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XXV, 850 p. 140 illus., 100 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Artificial Intelligence: Foundations, Theory, and Algorithms |
| Soggetto topico |
Uncertainty (Information theory)
Artificial intelligence |
| ISBN | 3-030-63153-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Part I: Theories of Uncertainty -- Belief Functions -- Understanding Belief Functions -- Reasoning with Belief Functions -- A Toolbox for the Working Scientist -- The Bigger Picture -- Part II: The Geometry of Uncertainty -- The Geometry of Belief Functions -- Geometry of Dempster's Rule -- Three Equivalent Models -- The Geometry of Possibility -- Part III: Geometry Interplays -- Probability Transforms: The Affine Family -- Probability Transforms: The Epistemic Family -- Consonant Approximation -- Consistent Approximation -- Part IV: Geometric Reasoning -- Geometric Conditioning -- Decision Making with Epistemic Transforms -- Part V The Future of Uncertainty -- An Agenda for the Future -- References. |
| Record Nr. | UNINA-9910484537503321 |
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Cuzzolin Fabio
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The geometry of uncertainty : the geometry of imprecise probabilities / / Fabio Cuzzolin
| The geometry of uncertainty : the geometry of imprecise probabilities / / Fabio Cuzzolin |
| Autore | Cuzzolin Fabio |
| Edizione | [1st ed. 2021.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (XXV, 850 p. 140 illus., 100 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Artificial Intelligence: Foundations, Theory, and Algorithms |
| Soggetto topico |
Uncertainty (Information theory)
Artificial intelligence |
| ISBN | 3-030-63153-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Part I: Theories of Uncertainty -- Belief Functions -- Understanding Belief Functions -- Reasoning with Belief Functions -- A Toolbox for the Working Scientist -- The Bigger Picture -- Part II: The Geometry of Uncertainty -- The Geometry of Belief Functions -- Geometry of Dempster's Rule -- Three Equivalent Models -- The Geometry of Possibility -- Part III: Geometry Interplays -- Probability Transforms: The Affine Family -- Probability Transforms: The Epistemic Family -- Consonant Approximation -- Consistent Approximation -- Part IV: Geometric Reasoning -- Geometric Conditioning -- Decision Making with Epistemic Transforms -- Part V The Future of Uncertainty -- An Agenda for the Future -- References. |
| Record Nr. | UNISA-996464398303316 |
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Cuzzolin Fabio
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| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Grey Systems and Intelligent Services, 2013 IEEE International Conference on / / IEEE Electrical Insulation Society Staff
| Grey Systems and Intelligent Services, 2013 IEEE International Conference on / / IEEE Electrical Insulation Society Staff |
| Pubbl/distr/stampa | Piscataway, NJ : , : IEEE, , 2013 |
| Descrizione fisica | 1 online resource (viii, 562 pages) |
| Disciplina | 003 |
| Soggetto topico |
System theory
Uncertainty (Information theory) |
| ISBN | 1-4673-5248-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
Proceedings of 2013 IEEE International Conference on Grey systems and Intelligent Services (GSIS)
Proceedings of 2013 IEEE International Conference on Grey systems and Intelligent Services |
| Record Nr. | UNINA-9910132408003321 |
| Piscataway, NJ : , : IEEE, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Grey Systems and Intelligent Services, 2013 IEEE International Conference on / / IEEE Electrical Insulation Society Staff
| Grey Systems and Intelligent Services, 2013 IEEE International Conference on / / IEEE Electrical Insulation Society Staff |
| Pubbl/distr/stampa | Piscataway, NJ : , : IEEE, , 2013 |
| Descrizione fisica | 1 online resource (viii, 562 pages) |
| Disciplina | 003 |
| Soggetto topico |
System theory
Uncertainty (Information theory) |
| ISBN | 1-4673-5248-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
Proceedings of 2013 IEEE International Conference on Grey systems and Intelligent Services (GSIS)
Proceedings of 2013 IEEE International Conference on Grey systems and Intelligent Services |
| Record Nr. | UNISA-996279288303316 |
| Piscataway, NJ : , : IEEE, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Guidelines for evaluating and expressing the uncertainty of NIST measurement results [[electronic resource] /] / Barry N. Taylor and Chris E. Kuyatt
| Guidelines for evaluating and expressing the uncertainty of NIST measurement results [[electronic resource] /] / Barry N. Taylor and Chris E. Kuyatt |
| Autore | Taylor B. N |
| Edizione | [1994 ed.] |
| Pubbl/distr/stampa | [Gaithersburg, Md.] : , : U.S. Department of Commerce, Technology Administration, National Institute of Standards and Technology, , 1994 |
| Descrizione fisica | 1 online resource (20 pages) |
| Altri autori (Persone) | KuyattChris E |
| Collana | NIST technical note |
| Soggetto topico |
Physical measurements - Standards - United States
Uncertainty (Information theory) |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910699335903321 |
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Taylor B. N
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| [Gaithersburg, Md.] : , : U.S. Department of Commerce, Technology Administration, National Institute of Standards and Technology, , 1994 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Handbook of uncertainty quantification / / Roger Ghanem, David Higdon, Houman Owhadi, editors
| Handbook of uncertainty quantification / / Roger Ghanem, David Higdon, Houman Owhadi, editors |
| Edizione | [1st ed. 2017.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2017] |
| Descrizione fisica | 1 online resource (520 illus., 424 illus. in color. eReference.) |
| Disciplina | 003.54 |
| Collana | Springer Reference |
| Soggetto topico | Uncertainty (Information theory) |
| ISBN | 3-319-12385-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preliminaries -- methodology.-sensitivity analysis -- forward problems -- risk -- codes of practise and factors of safety -- software. . |
| Record Nr. | UNINA-9910483811603321 |
| Cham, Switzerland : , : Springer, , [2017] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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How uncertainty-related ideas can provide theoretical explanation for empirical dependencies / / Martine Ceberio and Vladik Kreinovich (editors)
| How uncertainty-related ideas can provide theoretical explanation for empirical dependencies / / Martine Ceberio and Vladik Kreinovich (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (152 pages) : illustrations |
| Disciplina | 003.54 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico |
Justification (Theory of knowledge)
Uncertainty (Information theory) Incertesa (Teoria de la informació) Justificació (Teoria del coneixement) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-65324-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Status Quo Bias Actually Helps Decision Makers to Take Nonlinearity into Account: An Explanation -- 1 Formulation of the Problem -- 2 Analysis of the Problem and the Resulting Explanation -- References -- A Natural Explanation for the Minimum Entropy Production Principle -- 1 Formulation of the Problem -- 2 How Complex Problems Are Solved: Reminder and Related Analysis -- 3 How This Analysis Helps Explain the Minimum Entropy Production Principle -- References -- Why Class-D Audio Amplifiers Work Well: A Theoretical Explanation -- 1 Formulation of the Problem -- 2 Why Pulses -- 3 Why the Pulse's Duration Should Linearly Depend on the Amplitude of the Input Signal -- Reference -- How Can We Explain Different Number Systems? -- 1 Formulation of the Problem -- 2 Which Bases Appear if We Consider Divisibility by All Small Numbers from 1 to Some k -- 3 What if We Can Skip One Number -- 4 What if We Can Skip Two Numbers -- 5 What if We Can Skip Three or More Numbers -- References -- Why Immediate Repetition Is Good for Short-Time Learning Results but Bad for Long-Time Learning: Explanation Based on Decision Theory -- 1 Formulation of the Problem: How to Explain Recent Observations Comparing Long-Term Results of Immediate and Delayed Repetition -- 2 Main Idea Behind Our Explanation: Using Decision Theory -- 3 So When Do We Learn: Analysis of the Problem and the Resulting Explanation -- References -- Absence of Remotely Triggered Large Earthquakes: A Geometric Explanation -- 1 Formulation of the Problem -- 2 Geometric Explanation -- References -- Why Gamma Distribution of Seismic Inter-Event Times: A Theoretical Explanation -- 1 Formulation of the Problem -- 2 Our Explanation -- References -- Quantum Computing as a Particular Case of Computing with Tensors -- 1 Why Tensors -- 2 Tensors in Physics: A Brief Reminder.
3 From Tensors in Physics to Computing with Tensors -- 4 Modern Algorithm for Multiplying Large Matrices -- 5 Quantum Computing as Computing with Tensors -- 6 New Idea: Tensors to Describe Constraints -- 7 Computing with Tensors Can Also Help Physics -- 8 Remaining Open Problem -- References -- A ``Fuzzy'' Like Button Can Decrease Echo Chamber Effect -- 1 Formulation of the Problem -- 2 Proposed Solution -- References -- Intuitive Idea of Implication Versus Formal Definition: How to Define the Corresponding Degree -- 1 Formulation of the Problem -- 2 How to Define the Degree of Implication: A Seemingly Reasonable Idea and Its Limitations -- 3 Towards a New Definition of Degree of Implication -- References -- Dimension Compactification-A Possible Explanation for Superclusters and for Empirical Evidence Usually Interpreted as Dark Matter -- 1 Main Idea -- 2 Geometric Consequences of the Main Idea -- 3 Towards Physical Consequences of the Main Idea -- 4 Physical Consequences of the Main Idea -- 5 Observable Predictions of Our New Idea -- 6 Natural Open Questions -- References -- Fundamental Properties of Pair-Wise Interactions Naturally Lead to Quarks and Quark Confinement: A Theorem Motivated by Neural Universal Approximation Results -- 1 Formulation of the Problem -- 2 Definitions and the Main Result -- 3 Proof -- 4 Physical Interpretation of the Result -- References -- Linear Neural Networks Revisited: From PageRank to Family Happiness -- 1 Linear Neural Networks: A Brief Reminder -- 2 Linear Neural Networks: A Precise Description -- 3 Linear Neural Networks: From the General Case to the Simplest Case -- 4 First Application: PageRank Algorithm as an Example of a Linear Neural Network -- 5 Second Application: Family Dynamics -- References -- Why 3 Basic Colors? Why 4 Basic Tastes? -- 1 Introduction -- 2 Why 3 Basic Colors? -- 3 Why 4 Basic Tastes?. References -- What Segments Are the Best in Representing Contours? -- 1 Introduction to the Problem -- 2 Motivations of the Proposed Mathematical Definitions -- 3 Definitions and the Main Result -- 4 Proofs -- References -- Strength of Lime Stabilized Pavement Materials: Possible Theoretical Explanation of Empirical Dependencies -- 1 Formulation of the Problem -- 2 Our Explanation -- References -- Towards a Theoretical Explanation of How Pavement Condition Index Deteriorates over Time -- 1 Formulation of the Problem -- 2 General Invariances -- 3 First Attempt: Let Us Directly Apply Invariance Ideas to Our Problem -- 4 Let Us Now Apply Invariance Ideas Indirectly -- References -- A Recent Result About Random Metric Spaces Explains Why All of Us Have Similar Learning Potential -- 1 Formulation of the Problem -- 2 Our Explanation -- References -- Finitely Generated Sets of Fuzzy Values: If ``And'' Is Exact, Then ``Or'' Is Almost Always Approximate, and Vice Versa-A Theorem -- 1 Formulation of the Problem -- 2 Definitions and the Main Result -- 3 How General Is This Result? -- 4 What if We Allow Unlimited Number of ``And''-Operations and Negations: Case Study -- References -- Fuzzy Logic Explains the Usual Choice of Logical Operations in 2-Valued Logic -- 1 Formulation of the Problem -- 2 Our Explanation -- 3 Auxiliary Result: Why the Usual Quantifiers? -- References. |
| Record Nr. | UNINA-9910484321203321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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An inductive logic programming approach to statistical relational learning [[electronic resource] /] / Kristian Kersting
| An inductive logic programming approach to statistical relational learning [[electronic resource] /] / Kristian Kersting |
| Autore | Kersting Kristian |
| Pubbl/distr/stampa | Amsterdam ; ; Washington, D.C., : IOS Press, c2006 |
| Descrizione fisica | 1 online resource (256 p.) |
| Collana |
Frontiers in artificial intelligence and applications
Dissertations in artificial intelligence |
| Soggetto topico |
Logic programming
Uncertainty (Information theory) Machine learning Markov processes |
| Soggetto genere / forma | Electronic books. |
| ISBN |
6610704821
1-280-70482-9 9786610704828 1-4294-5527-6 1-60750-207-0 600-00-0341-2 1-4337-0124-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Title page; Contents; Abstract; Overture; Part I: Probabilistic ILP over Interpretations; Part II: Probabilistic ILP over Time; Intermezzo: Exploiting Probabilistic ILP in Discriminative Classifiers; Part III: Making Complex Decisions in Relational Domains; Finale; Appendix; Bibliography; Symbol Index; Index |
| Record Nr. | UNINA-9910450851303321 |
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Kersting Kristian
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| Amsterdam ; ; Washington, D.C., : IOS Press, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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