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Theory and Applications of Formal Argumentation

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Cover of 'Theory and Applications of Formal Argumentation'

Table of Contents

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    Book Overview
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    Chapter 1 Comparing and Integrating Argumentation-Based with Matrix-Based Decision Support in Arg&Dec
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    Chapter 2 Reasons and Options for Updating an Opponent Model in Persuasion Dialogues
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    Chapter 3 Abstract Solvers for Dung’s Argumentation Frameworks
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    Chapter 4 A Discussion Game for Grounded Semantics
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    Chapter 5 An Axiomatic Approach to Support in Argumentation
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    Chapter 6 Non-Monotonic Inference Properties for Assumption-Based Argumentation
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    Chapter 7 On Explanations for Non-Acceptable Arguments
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    Chapter 8 Building Support-Based Opponent Models in Persuasion Dialogues
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    Chapter 9 The Hidden Power of Abstract Argumentation Semantics
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    Chapter 10 Argument Mining: A Machine Learning Perspective
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    Chapter 11 Arguing from Similar Positions: An Empirical Analysis
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    Chapter 12 ArgP2P: An Argumentative Approach for Intelligent Query Routing in P2P Networks
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    Chapter 13 Persistence and Monotony Properties of Argumentation Semantics
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    Chapter 14 Argumentation-based Normative Practical Reasoning
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    Chapter 15 The Matrix Approach for Abstract Argumentation Frameworks
Attention for Chapter 13: Persistence and Monotony Properties of Argumentation Semantics
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Summary
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Chapter title
Persistence and Monotony Properties of Argumentation Semantics
Chapter number 13
Book title
Theory and Applications of Formal Argumentation
Published by
Springer, Cham, July 2015
DOI 10.1007/978-3-319-28460-6_13
Book ISBNs
978-3-31-928459-0, 978-3-31-928460-6
Authors

Tjitze Rienstra, Chiaki Sakama, Leendert van der Torre

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 33%
Student > Master 2 33%
Student > Ph. D. Student 1 17%
Unknown 1 17%
Readers by discipline Count As %
Computer Science 5 83%
Unknown 1 17%

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