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Abductive Reasoning

Douglas Walton

Publication Year: 2014

This book examines three areas in which abductive reasoning is especially important: medicine, science, and law. The reader is introduced to abduction and shown how it has evolved historically into the framework of conventional wisdom in logic. Discussions draw upon recent techniques used in artificial intelligence, particularly in the areas of multi-agent systems and plan recognition, to develop a dialogue model of explanation. Cases of causal explanations in law are analyzed using abductive reasoning, and all the components are finally brought together to build a new account of abductive reasoning.  

By clarifying the notion of abduction as a common and significant type of reasoning in everyday argumentation, Abductive Reasoning will be useful to scholars and students in many fields, including argumentation, computing and artificial intelligence, psychology and cognitive science, law, philosophy, linguistics, and speech communication and rhetoric.

 

Published by: The University of Alabama Press

Cover

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Title Page, Copyright, Dedication

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Contents

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pp. vii-x

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Acknowledgments

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pp. xi-xii

I would like to thank the Social Sciences and Humanities Research Council of Canada for a research grant that made writing this book possible. The motivation to tackle abduction as an important research topic for both argumentation and computing was stimulated by participation in the Symposium on Argument and Computation at Bonskeid House in Perthshire, Scotland, in June and July of 2000. ...

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Introduction

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pp. xiii-xvi

Abductive inference, commonly called inference to the best explanation, is reasoning from given data to a hypothesis that explains the data. Abductive inference is very common in forensic evidence. For example, if pieces of a knife blade are found in the window frame of a house where a burglary occurred, the best explanation may be that entry took place by someone's prying open the window with a knife. ...

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1. Abductive, Presumptive, and Plausible Arguments

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pp. 1-50

Three kinds of inference—abductive argument, presumptive argument, and plausible argument—are often confused. And it is not too surprising that they are confused. They seem to be quite similar in representing a kind of uncertain and tentative reasoning that is very common in everyday thinking, ...

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2. A Dialogue Model of Explanation

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pp. 51-96

Lipton (1991, p. 2) wondered why inference to the best explanation has been so little developed as a theoretical model of reasoning, given its evident importance and popularity in so many fields. He suggested (p. 2) the following reason: ...

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3. A Procedural Model of Rationality

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pp. 97-121

Any attempt to analyze abductive reasoning and to define it as a distinctive type of reasoning to be contrasted with deductive and inductive reasoning raises fundamental questions for logic as a discipline. In chapter 1, we saw that AI systems use forward chaining of reasoning from a given database or set of "facts" using a set of rules to generate conclusions derived from the facts. ...

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4. Defeasible Modus Ponens Arguments

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pp. 122-157

In chapter 3, it was shown how reasoning typically takes the form of a forward chaining of defeasible modus ponens inferences that are not deductively valid. It is argued in chapter 4 that many common arguments used in everyday reasoning have the form modus ponens or a form similar to modus ponens but are not deductively valid. ...

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5. Abductive Causal Reasoning

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pp. 158-205

Causation is an unsolved problem that affects fields as diverse as science, law, medicine, and history. The measles inference in chapter 4 indicated how common causal explanations are in medicine and how important they are to proper medical diagnosis and treatment. ...

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6. Query-Driven Abductive Reasoning

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pp. 206-242

Chapter 6 analyzes abduction as a query-driven form of inference to the best explanation in which the conversational context of an abductive chain of reasoning must be considered. According to this theory, the structural correctness of an abductive inference depends on the transfer of understanding from one party to another in a dialogue. ...

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7. Unsolved Problems of Abduction

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pp. 243-276

The aim of chapter 7 is to provide a platform for further research on abductive reasoning by indicating some key areas where problems need to be solved but where the dialectical theory of abduction as inference to the best explanation makes gains. It is easy to see that the theory put forward in chapter 6 cannot solve all the problems that have been raised. ...

Notes

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pp. 277-282

References

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pp. 283-294

Index

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pp. 295-303


E-ISBN-13: 9780817387617
E-ISBN-10: 0817387617
Print-ISBN-13: 9780817314415
Print-ISBN-10: 0817314415

Page Count: 319
Illustrations: 13 illustrations
Publication Year: 2014

OCLC Number: 879576359
MUSE Marc Record: Download for Abductive Reasoning