Abduction and Induction

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.