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Judgment aggregation : : a primer /

By: Grossi, Davide [author.].
Contributor(s): Pigozzi, Gabriella [author.].
Material type: materialTypeLabelBookSeries: Synthesis digital library of engineering and computer science: ; Synthesis lectures on artificial intelligence and machine learning: # 27.Publisher: San Rafael, California (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, 2014.Description: 1 PDF (xvii, 133 pages).Content type: text Media type: electronic Carrier type: online resourceISBN: 9781627050883.Subject(s): Aggregation operators | Judgment -- Data processing | Group decision making -- Data processing | Artificial intelligence -- Data processing | judgment aggregation | collective decision-making | logic | social choice theory | computational social choice | preference aggregation | voting paradoxes | aggregation rules | impossibility results | manipulability | ultrafilters | opinion pooling | deliberationDDC classification: 515.724 Online resources: Abstract with links to resource | Abstract with links to full text Also available in print.
Contents:
1. Logic meets social choice theory -- 1.1 A concise history of social choice theory -- 1.1.1 The early history -- 1.1.2 Modern social choice theory -- 1.2 A new type of aggregation -- 1.2.1 From the doctrinal paradox to the discursive dilemma -- 1.2.2 Preference aggregation and judgment aggregation -- 1.3 Further topics --
2. Basic concepts -- 2.1 Preliminaries -- 2.1.1 Agendas in propositional logic -- 2.1.2 Judgment sets and profiles -- 2.1.3 Aggregation functions -- 2.1.4 Examples: aggregation rules -- 2.2 Agenda conditions -- 2.2.1 How interconnected is an agenda? -- 2.2.2 Comparing agenda conditions -- 2.3 Aggregation conditions -- 2.3.1 How should an aggregation function behave? -- 2.3.2 On the meaning of the aggregation conditions -- 2.4 Further topics -- 2.4.1 Abstract aggregation -- 2.4.2 General logics --
3. Impossibility -- 3.1 What is the majority rule like? -- 3.1.1 Properties of propositionwise majority -- 3.1.2 Characterizing propositionwise majority -- 3.2 An impossibility theorem -- 3.2.1 Winning coalitions -- 3.2.2 Winning coalitions as ultrafilters -- 3.2.3 Dictators -- 3.2.4 The theorem -- 3.3 (Ultra)filters, dictators and oligarchs -- 3.3.1 Impossibility of non-oligarchic aggregation -- 3.3.2 Proof: from ultrafilters to filters -- 3.3.3 Impossibility via (ultra)filters -- 3.4 Further topics -- 3.4.1 Other impossibility results -- 3.4.2 Infinite agendas and infinite voters -- 3.4.3 Judgment aggregation vs. preference aggregation --
4. Coping with impossibility -- 4.1 Relaxing universal domain -- 4.1.1 Unidimensional alignment -- 4.1.2 Value-restriction -- 4.2 Relaxing the output conditions -- 4.2.1 Abstention -- 4.2.2 Quota rules -- 4.3 Relaxing independence -- 4.3.1 The premise-based approach -- 4.3.2 The sequential priority approach -- 4.3.3 The distance-based rules -- 4.4 Further topics -- 4.4.1 More domain restrictions -- 4.4.2 Dropping consistency -- 4.4.3 Other distance-based rules -- 4.4.4 Judgment aggregation and abstract argumentation --
5. Manipulability -- 5.1 Types of manipulation -- 5.1.1 Agenda manipulation -- 5.1.2 Vote manipulation -- 5.1.3 Manipulability: definition and characterization -- 5.1.4 Sincere and insincere manipulation -- 5.2 Non-manipulable aggregation: impossibility -- 5.2.1 Auxiliary results -- 5.2.2 The impossibility theorem -- 5.3 Further topics: manipulation beyond impossibility results -- 5.3.1 The possibility of non-manipulable aggregation -- 5.3.2 Strategy-proof judgment aggregation -- 5.3.3 Complexity as a safeguard against manipulation --
6. Aggregation rules -- 6.1 Introduction -- 6.2 Rules based on the majoritarian judgment set -- 6.3 Rules based on the weighted majoritarian judgment set -- 6.4 Rules based on the removal or change of individual judgments -- 6.5 Further topics --
7. Deliberation -- 7.1 Deliberation and opinion pooling -- 7.1.1 Probabilistic judgments -- 7.1.2 A stochastic model of deliberation -- 7.1.3 Opinion pooling and judgment aggregation -- 7.2 Deliberation as judgment transformation -- 7.2.1 Deliberation and voting -- 7.2.2 Judgment transformation functions -- 7.2.3 Examples of transformation functions -- 7.3 Limits of judgment transformation -- 7.3.1 Conditions on transformation functions -- 7.3.2 An impossibility result -- 7.4 Further topics and open issues --
Bibliography -- Authors' biographies -- Index.
Abstract: Judgment aggregation is a mathematical theory of collective decision-making. It concerns the methods whereby individual opinions about logically interconnected issues of interest can, or cannot, be aggregated into one collective stance. Aggregation problems have traditionally been of interest for disciplines like economics and the political sciences, as well as philosophy, where judgment aggregation itself originates from, but have recently captured the attention of disciplines like computer science, artificial intelligence and multi-agent systems. Judgment aggregation has emerged in the last decade as a unifying paradigm for the formalization and understanding of aggregation problems. Still, no comprehensive presentation of the theory is available to date. This Synthesis Lecture aims at filling this gap presenting the key motivations, results, abstractions and techniques underpinning it.
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E books E books PK Kelkar Library, IIT Kanpur
Available EBKE559
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Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (pages 111-127) and index.

1. Logic meets social choice theory -- 1.1 A concise history of social choice theory -- 1.1.1 The early history -- 1.1.2 Modern social choice theory -- 1.2 A new type of aggregation -- 1.2.1 From the doctrinal paradox to the discursive dilemma -- 1.2.2 Preference aggregation and judgment aggregation -- 1.3 Further topics --

2. Basic concepts -- 2.1 Preliminaries -- 2.1.1 Agendas in propositional logic -- 2.1.2 Judgment sets and profiles -- 2.1.3 Aggregation functions -- 2.1.4 Examples: aggregation rules -- 2.2 Agenda conditions -- 2.2.1 How interconnected is an agenda? -- 2.2.2 Comparing agenda conditions -- 2.3 Aggregation conditions -- 2.3.1 How should an aggregation function behave? -- 2.3.2 On the meaning of the aggregation conditions -- 2.4 Further topics -- 2.4.1 Abstract aggregation -- 2.4.2 General logics --

3. Impossibility -- 3.1 What is the majority rule like? -- 3.1.1 Properties of propositionwise majority -- 3.1.2 Characterizing propositionwise majority -- 3.2 An impossibility theorem -- 3.2.1 Winning coalitions -- 3.2.2 Winning coalitions as ultrafilters -- 3.2.3 Dictators -- 3.2.4 The theorem -- 3.3 (Ultra)filters, dictators and oligarchs -- 3.3.1 Impossibility of non-oligarchic aggregation -- 3.3.2 Proof: from ultrafilters to filters -- 3.3.3 Impossibility via (ultra)filters -- 3.4 Further topics -- 3.4.1 Other impossibility results -- 3.4.2 Infinite agendas and infinite voters -- 3.4.3 Judgment aggregation vs. preference aggregation --

4. Coping with impossibility -- 4.1 Relaxing universal domain -- 4.1.1 Unidimensional alignment -- 4.1.2 Value-restriction -- 4.2 Relaxing the output conditions -- 4.2.1 Abstention -- 4.2.2 Quota rules -- 4.3 Relaxing independence -- 4.3.1 The premise-based approach -- 4.3.2 The sequential priority approach -- 4.3.3 The distance-based rules -- 4.4 Further topics -- 4.4.1 More domain restrictions -- 4.4.2 Dropping consistency -- 4.4.3 Other distance-based rules -- 4.4.4 Judgment aggregation and abstract argumentation --

5. Manipulability -- 5.1 Types of manipulation -- 5.1.1 Agenda manipulation -- 5.1.2 Vote manipulation -- 5.1.3 Manipulability: definition and characterization -- 5.1.4 Sincere and insincere manipulation -- 5.2 Non-manipulable aggregation: impossibility -- 5.2.1 Auxiliary results -- 5.2.2 The impossibility theorem -- 5.3 Further topics: manipulation beyond impossibility results -- 5.3.1 The possibility of non-manipulable aggregation -- 5.3.2 Strategy-proof judgment aggregation -- 5.3.3 Complexity as a safeguard against manipulation --

6. Aggregation rules -- 6.1 Introduction -- 6.2 Rules based on the majoritarian judgment set -- 6.3 Rules based on the weighted majoritarian judgment set -- 6.4 Rules based on the removal or change of individual judgments -- 6.5 Further topics --

7. Deliberation -- 7.1 Deliberation and opinion pooling -- 7.1.1 Probabilistic judgments -- 7.1.2 A stochastic model of deliberation -- 7.1.3 Opinion pooling and judgment aggregation -- 7.2 Deliberation as judgment transformation -- 7.2.1 Deliberation and voting -- 7.2.2 Judgment transformation functions -- 7.2.3 Examples of transformation functions -- 7.3 Limits of judgment transformation -- 7.3.1 Conditions on transformation functions -- 7.3.2 An impossibility result -- 7.4 Further topics and open issues --

Bibliography -- Authors' biographies -- Index.

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

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Judgment aggregation is a mathematical theory of collective decision-making. It concerns the methods whereby individual opinions about logically interconnected issues of interest can, or cannot, be aggregated into one collective stance. Aggregation problems have traditionally been of interest for disciplines like economics and the political sciences, as well as philosophy, where judgment aggregation itself originates from, but have recently captured the attention of disciplines like computer science, artificial intelligence and multi-agent systems. Judgment aggregation has emerged in the last decade as a unifying paradigm for the formalization and understanding of aggregation problems. Still, no comprehensive presentation of the theory is available to date. This Synthesis Lecture aims at filling this gap presenting the key motivations, results, abstractions and techniques underpinning it.

Also available in print.

Title from PDF title page (viewed on April 21, 2014).

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