Working with Preferences: Less Is More: less is more
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
Springer Berlin
2013
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| Schriftenreihe: | Cognitive Technologies
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| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XVI, 202 Seiten Diagramme 235 mm x 155 mm |
| ISBN: | 9783642268830 3642268838 |
Internformat
MARC
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Datensatz im Suchindex
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Contents 1 Introduction. 1 Part I Preferences Modeling andRepresentation 2 Preferences Modeling. 2.1 Introduction. 2.2 Crisp Preference Relations. 2.3 Fuzzy Preference Relations. 2.4 The Language . References. 11 11 12 15 16 16 3 Preference Representation Languages. 3.1 Introduction. 3.2 Numerical Language. 3.3 Weighted Logics. 3.3.1 Penalty Logic. 3.3.2 Distance-Based Closeness to Preferences. 3.3.3 Possibilistic Logic . 3.3.4 Discrimin and LexicographicalOrderings. 3.3.5 Guaranteed
Possibilistic Logic. 3.3.6 Qualitative Choice Logic. 3.3.7 Partially Ordered Formulas. 3.4 Conditional Logics. 3.4.1 Preference Semantics. 3.4.2 From a Preference Set to a Preference Relation. 3.4.3 Strong and Ceteris Paribus Semantics. 3.4.4 Optimistic Semantics. 3.4.5 Pessimistic Semantics . 3.4.6 Opportunistic Semantics. 3.4.7 Beyond Semantics. 3.4.8 Related Work . 19 19 20 21 24 25 26 32 34 36 37 38 38 41 42 45 46 48 48 50 xi
Contents xii 3.4.9 Advanced Logics for Comparative Preference Statements . Graphical Languages . 3.5.1 Generalized Additive Independence Networks. 3.5.2 Conditional Preference Networks. 3.5.3 Conditional Preference Networks with Tradeoffs. 3.5.4 Conditional Importance Networks. 3.5.5 Conditional Preference Networks with Utilities. 3.5.6 Soft Constraint Satisfaction Problems. 3.6 Bipolar Preferences. 3.6.1 Representing Bipolar Preferencesin Weighted Logics. 3.6.2 Representing Bipolar Preferences in Conditional Logics. 3.6.3 Representing Bipolar Preferences in Graphical Languages . 3.7 Conclusion. References. 3.5 54 61 61 64 70 71 72 72 76 76 79 80 81 81 4 . Making Hidden Priorities Explicit . 87 4.1 Introduction. 87 4.2 Conditional Logics and Weighted Logics. 88 4.2.1 Optimistic Semantics vs. Prioritized Preferences. 88 4.2.2 Strong
Semantics vs. Prioritized Preferences . 92 4.2.3 Pessimistic Semantics vs. Prioritized Preferences . 95 4.3 Positive and Negative Preferences. 96 4.4 Conditional Preference Networks and Weighted Preferences. 99 4.5 Conclusion.104 References.104 5 What Psychology Has to Say About Preferences.107 5.1 Introduction.107 5.2 Origins of Preferences .108 5.3 The Role of Affect in Human Preferences.109 5.4 The Constructive Nature of Preferences.Ill 5.5 Conclusion.114 References.114 Part II Reasoning with Preferences 6 Preferences in Argumentation Theory.121 6.1 Introduction.121 6.2 Dung’s Argumentation
Framework.122 6.3 Preference-Based Argumentation Framework. 125 6.4 Where Does the Preference Relation Comefrom? . 132 6.4.1 Implicit Priorities.132 6.4.2 Explicit Priorities.133 6.4.3 Value-Based Argumentation Framework.134 6.4.4 Extended Value-Based Argumentation Framework.136 6.4.5 Arguing About Preferences. 138
xiii Contents 6.4.6 Preference-Based Argumentation Framework with Fuzzy Preference Relation.139 6.5 Higher Use of Preferences in Preference-Based Argumentation Frameworks.145 6.6 Conclusion.148 References.149 7 Preferences in Database Queries.151 7.1 Introduction.151 7.2 Preliminaries.152 7.3 Database Queries with Preferences.153 7.4 Database Queries with the .Skyline Operator. 153 7.5 Database Queries with Preference Constructors . 155 7.6 Database Queries with Logical Formulas. 155 7.7 Database Queries with a CP-net .158 7.8 Database Queries with an Incomplete CP-net.160 7.9 Database Queries with Comparative Preference Statements.161 7.10
Conclusion.166 References.166 8 Preferences Aggregation.173 8.1 Introduction.173 8.2 Multiple Criteria Decision.175 8.2.1 Multiple Aggregation Decision vs. Conditional Logics.176 8.2.2 Numerical AggregationApproach: Discrete Choquet Integral. 179 8.2.3 Conditional Logics vs. Choquet Integral.181 8.3 Temporal Reasoning.185 8.3.1 Qualitative Interval Algebra.186 8.3.2 Conditional Logics vs. Allen’s Algebra.188 8.4 Conclusion.192 References.192 9 Conclusion. 195 Index 201 |
| any_adam_object | 1 |
| author | Kaci, Souhila |
| author_facet | Kaci, Souhila |
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| ctrlnum | (OCoLC)1085390011 (DE-599)DNB1038120128 |
| discipline | Informatik |
| format | Book |
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| title | Working with Preferences: Less Is More less is more |
| title_auth | Working with Preferences: Less Is More less is more |
| title_exact_search | Working with Preferences: Less Is More less is more |
| title_full | Working with Preferences: Less Is More less is more Souhila Kaci |
| title_fullStr | Working with Preferences: Less Is More less is more Souhila Kaci |
| title_full_unstemmed | Working with Preferences: Less Is More less is more Souhila Kaci |
| title_short | Working with Preferences: Less Is More |
| title_sort | working with preferences less is more less is more |
| title_sub | less is more |
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| topic_facet | Künstliche Intelligenz Logik Schlussfolgern Präferenz Abfrageverarbeitung Entscheidungstheorie Logischer Schluss |
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