Abduction and Induction

1. Front Matter

   Pages i-xix

   PDF

2. Abductive and Inductive Reasoning: Background and Issues

   1. Abductive and Inductive Reasoning: Background and Issues

      • Peter A. Flach, Antonis C. Kakas

      Pages 1-27

3. The philosophy of abduction and induction

   1. Front Matter

      Pages 29-29

      PDF

   2. Smart Inductive Generalizations are Abductions

      • John R. Josephson

      Pages 31-44

   3. Abduction as Epistemic Change: A Peircean Model in Artificial Intelligence

      • Atocha Aliseda

      Pages 45-58

   4. Abduction: Between Conceptual Richness and Computational Complexity

      • Stathis Psillos

      Pages 59-74

4. The logic of abduction and induction

   1. Front Matter

      Pages 75-75

      PDF

   2. On Relationships between Induction and Abduction: A Logical Point of View

      • Brigitte Bessant

      Pages 77-87

   3. On the Logic of Hypothesis Generation

      • Peter A. Flach

      Pages 89-106

   4. Abduction and Induction from a Non-Monotonic Reasoning Perspective

      • Nicolas Lachiche

      Pages 107-116

   5. Unified Inference in Extended Syllogism

      • Pei Wang

      Pages 117-129

5. The integration of abduction and induction: an Artificial Intelligence perspective

   1. Front Matter

      Pages 131-131

      PDF

   2. On the Relations between Abductive and Inductive Explanation

      • Luca Console, Lorenza Saitta

      Pages 133-151

   3. Learning, Bayesian Probability, Graphical Models, and Abduction

      • David Poole

      Pages 153-168

   4. On the Relation between Abductive and Inductive Hypotheses

      • Akinori Abe

      Pages 169-180

   5. Integrating Abduction and Induction in Machine Learning

      • Raymond J. Mooney

      Pages 181-191

6. The integration of abduction and induction: a Logic Programming perspective

   1. Front Matter

      Pages 193-193

      PDF

   2. Abduction and Induction Combined in a Metalogic Framework

      • Henning Christiansen

      Pages 195-211

   3. Learning Abductive and Nonmonotonic Logic Programs

      • Katsumi Inoue, Hiromasa Haneda

      Pages 213-231

   4. Cooperation of Abduction and Induction in Logic Programming

      • Evelina Lamma, Paola Mello, Fabrizio Riguzzi, Floriana Esposito, Stefano Ferilli, Giovanni Semeraro

      Pages 233-252

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.

• artificial intelligence
• complexity
• computer
• intelligence
• learning
• logic
• machine learning
• nonmonotonic reasoning
• probability
• programming

`The present book ... does throw open windows towards understanding the true complexities of reasoning, by presenting abduction and induction intertwined as a fascinating case study for `real logic'.'
Johan van Benthem, University of Amsterdam

• University of Bristol, UK

  Peter A. Flach

• University of Cyprus, Cyprus

  Antonis C. Kakas

Policies and ethics