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Abduction and Induction

Overview of attention for book
Cover of 'Abduction and Induction'

Table of Contents

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    Book Overview
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    Chapter 1 Abductive and Inductive Reasoning: Background and Issues
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    Chapter 2 Smart Inductive Generalizations are Abductions
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    Chapter 3 Abduction as Epistemic Change: A Peircean Model in Artificial Intelligence
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    Chapter 4 Abduction: Between Conceptual Richness and Computational Complexity
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    Chapter 5 On Relationships between Induction and Abduction: A Logical Point of View
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    Chapter 6 On the Logic of Hypothesis Generation
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    Chapter 7 Abduction and Induction from a Non-Monotonic Reasoning Perspective
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    Chapter 8 Unified Inference in Extended Syllogism
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    Chapter 9 On the Relations between Abductive and Inductive Explanation
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    Chapter 10 Learning, Bayesian Probability, Graphical Models, and Abduction
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    Chapter 11 On the Relation between Abductive and Inductive Hypotheses
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    Chapter 12 Integrating Abduction and Induction in Machine Learning
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    Chapter 13 Abduction and Induction Combined in a Metalogic Framework
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    Chapter 14 Learning Abductive and Nonmonotonic Logic Programs
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    Chapter 15 Cooperation of Abduction and Induction in Logic Programming
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    Chapter 16 Abductive Generalization and Specialization
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    Chapter 17 Using Abduction for Induction Based on Bottom Generalization
Attention for Chapter 8: Unified Inference in Extended Syllogism
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Citations

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Chapter title
Unified Inference in Extended Syllogism
Chapter number 8
Book title
Abduction and Induction
Published by
Springer, Dordrecht, January 2000
DOI 10.1007/978-94-017-0606-3_8
Book ISBNs
978-9-04-815433-3, 978-9-40-170606-3
Authors

Pei Wang

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 33%
Unknown 2 67%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Student > Ph. D. Student 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Philosophy 1 33%

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