David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Cambridge University Press (1994)
In informal terms, abductive reasoning involves inferring the best or most plausible explanation from a given set of facts or data. It is a common occurrence in everyday life and crops up in such diverse places as medical diagnosis, scientific theory formation, accident investigation, language understanding, and jury deliberation. In recent years, it has become a popular and fruitful topic in artificial intelligence research. This volume breaks new ground in the scientific, philosophical, and technological study of abduction. It 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 non-inferentially, or that deduction and inductive generalization are enough to account for knowledge. Much AI research is hypothetical, so the importance of this book is that it reports key discoveries about abduction that have been made as a result of designing, building, testing, and analyzing actual working knowledge-based systems for medical diagnosis and other abductive tasks. The book tells the story of six generations of increasingly sophisticated generic abduction machines, RED-1, RED-2, PEIRCE, MDX2, TIPS, QUAWDS, and the discovery of reasoning strategies that make it computationally feasible to form well-justified composite explanatory hypotheses, despite the threat of combinatorial explosion. The final chapter argues that perception is logically abductive and presents a layered-abduction computational model of perceptual information processing. This book will be of great interest to researchers in AI, cognitive science, and philosophy of science.
|Keywords||Abduction (Logic Inference Knowledge, Theory of|
|Categories||categorize this paper)|
|Buy the book||$8.45 used (95% off) $38.00 new (37% off) $59.99 direct from Amazon Amazon page|
|Call number||BC199.A26.J67 1994|
|ISBN(s)||0521434610 0521575451 9780521575454|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
David C. Gooding (2010). Visualizing Scientific Inference. Topics in Cognitive Science 2 (1):15-35.
Guy Politzer (2007). Reasoning with Conditionals. Topoi 26 (1):79-95.
Jun-Young Oh (2014). Understanding Natural Science Based on Abductive Inference: Continental Drift. [REVIEW] Foundations of Science 19 (2):153-174.
D. Walton & C. A. Reed (2005). Argumentation Schemes and Enthymemes. Synthese 145 (3):339 - 370.
Similar books and articles
John Woods (2007). Ignorance and Semantic Tableaux: Aliseda on Abduction. Theoria 22 (3):305-318.
Cameron Shelley (1996). Visual Abductive Reasoning in Archaeology. Philosophy of Science 63 (2):278-301.
Ilkka Niiniluoto (1999). Defending Abduction. Philosophy of Science 66 (3):451.
Michael Hoffmann (1999). Problems with Peirce's Concept of Abduction. Foundations of Science 4 (3):271-305.
Dov Gabbay & John Woods (2006). Advice on Abductive Logic. Logic Journal of the Igpl 14 (2):189-219.
Tomis Kapitan (1992). Peirce and the Autonomy of Abductive Reasoning. Erkenntnis 37 (1):1 - 26.
Atocha Aliseda (2007). Abductive Reasoning: Challenges Ahead. Theoria 22 (3):261-270.
Sami Paavola (2011). Abductive Cognition: The Epistemological and Eco-Cognitive Dimensions of Hypothetical Reasoning (Review). Transactions of the Charles S. Peirce Society 47 (2):252-256.
Sami Paavola (2004). Abduction as a Logic and Methodology of Discovery: The Importance of Strategies. [REVIEW] Foundations of Science 9 (3):267-283.
Added to index2009-01-28
Total downloads25 ( #118,814 of 1,724,890 )
Recent downloads (6 months)1 ( #349,138 of 1,724,890 )
How can I increase my downloads?