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Abduction and Induction

 

You are here: Computing & Internet > Applications Of Computing > Artificial Intelligence 

Word Power Books

Abduction and Induction


Peter Flach (Editor)
Antonis C. Kakas (Editor)

 

Paperback

ISBN: 9789048154333

 

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Our Price: £162.00

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From the very beginning of their investigation of human reasoning, philosophers have identified two other forms of reasoning, besides deduction, which we now call abduction and induction. Deduction is now fairly well understood, but abduction and induction have eluded a similar level of understanding. The papers collected here address the relationship between abduction and induction and their possible integration. The approach is sometimes philosophical, sometimes that of pure logic, and some papers adopt the more task-oriented approach of AI. The book will command the attention of philosophers, logicians, AI researchers and computer scientists in general.


 

ISBN 9048154332
ISBN13 9789048154333
Publisher Springer
Format Paperback
Publication date 15/12/2010
Pages 336
Weight (grammes) 503
Published in Netherlands
Height (mm) 240
Width (mm) 160

Foreword. Preface. Contributing Authors. 1. Abductive
and inductive reasoning: background and issues
P.A. Flach, A.C.
Kakas. Part I: The philosophy of abduction and induction.
2. Smart inductive generalizations are abductions
J.R.
Josephson. 3. Abduction as epistemic change: a Peircean
model in Artificial Intelligence
A. Aliseda. 4.
Abduction: between conceptual richness and computational complexity

S. Psillos. Part II: The logic of abduction and
induction. 5. On relationships between induction and
abduction: a logical point of view
B. Bessant. 6. On the
logic of hypothesis generation
P.A. Flach. 7. Abduction
and induction from a non-monotonic reasoning perspective
N.
Lachiche. 8. Unified inference in extended syllogism
P.
Wang. Part III: The integration of abduction and
induction: an Artificial Intelligence perspective. 9.
On the relations between abductive and inductive explanation
L.
Console, L. Saitta. 10. Learning, Bayesian probability,
graphical models, and abduction
D. Poole. 11. On
the relation between abductive and inductive hypotheses
A. Abe.
12. Integrating abduction and induction in Machine Learning

R.J. Mooney. Part IV: The integration of abduction and
induction: a Logic Programming perspective. 13.
Abduction and induction combined in a metalogic framework
H.
Christiansen. 14. Learning abductive and nonmonotonic logic
programs
K. Inoue, H. Haneda. 15. Cooperation of
abduction and induction in Logic Programming
E. Lamma, et al.
16. Abductive generalization and specialization
C.
Sakama. 17. Using abduction for induction based on bottom
generalization
A. Yamamoto. Bibliography. Index.