Synopses & Reviews
In informal terms, abductive reasoning involves inferring the best or most plausible explanation from a given set of facts or data. This volume presents new ideas about inferential and information-processing foundations for knowledge and certainty. The authors argue that knowledge arises from experience by processes of abductive inference, in contrast to the view that it arises noninferentially, or that deduction and inductive generalization are enough to account for knowledge. The book tells the story of six generations of increasingly sophisticated generic abduction machines and the discovery of reasoning strategies that make it computationally feasible to form well-justified composite explanatory hypotheses, despite the threat of combinatorial explosion. This book will be of great interest to researchers in AI, cognitive science, and philosophy of science.
Review
"This book breaks new ground in the scientific, philosophical, and technological study of abduction." Peirce Project Newsletter
Synopsis
This volume makes significant progress in analysing abduction as an information-processing phenomenon, and in describing how AI systems can be built for abductive tasks such as diagnosis.
Synopsis
This book is about abduction, âthe logic of Sherlock Holmesâ, and about how some kinds of abductive reasoning can be programmed in a computer. The work brings together Artificial Intelligence and philosophy of science and is rich with implications for other areas such as psychology, medical informatics, and linguistics. It also has subtle implications for evidence evaluation in areas such as accident investigation, confirmation of scientific theories, law, diagnosis, and financial auditing. The book is about certainty and the logico-computational foundations of knowledge; it is about inference in perception, reasoning strategies, and building expert systems.
Synopsis
Abductive reasoning involves inferring the best or most plausible explanation from a given set of facts or data. Arguing that knowledge arises from experience by processes of abductive interence, this volume presents new ideas about inferential and information-processing foundations for knowledge and certainty.
Table of Contents
Introduction; 1. Conceptual analysis of abduction: what is abduction?; 2. Knowledge-based systems and the science of AI: 3. Two RED systems; 4. Generalizing the control strategy; 5. More kinds of knowledge: TIPS and PATHEX/LIVER TIPS; 6. Better task analysis, better strategy; 7. Computational complexity of abduction; 8. Diagnostic systems MDX2 and QUADS; 9. Practical abduction; 10. Perception and language understanding; Appendices.