From the very beginning of their investigation of human reasoning, philosophers have identified two other forms of reasoning, besides deduction, which is called as abduction and induction. This book addresses the relationship between abduction and induction and their possible integration, and is for philosophers, logicians, and AI researchers.

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.

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.