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Induction: Processes of Inference, Learning, and Discovery
 
 
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Induction: Processes of Inference, Learning, and Discovery [Paperback]

John H. Holland (Author), Keith J. Holyoak (Author), Richard E. Nisbett (Author), Paul Thagard (Author)
4.5 out of 5 stars  See all reviews (2 customer reviews)

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Book Description

March 2, 1989 Computational Models of Cognition and Perception

Two psychologists, a computer scientist, and a philosopher have collaborated to present a framework for understanding processes of inductive reasoning and learning in organisms and machines. Theirs is the first major effort to bring the ideas of several disciplines to bear on a subject that has been a topic of investigation since the time of Socrates. The result is an integrated account that treats problem solving and induction in terms of rule­based mental models.John Holland is Professor of Electrical Engineering at Michigan University. Keith Holyoak is Professor of Psychology at the University of California, Los Angeles. Richard Nisbett is Professor of Psychology at the University of Michigan and Paul Thagard is Research Scientist at Princeton University's Cognitive Science Laboratory Induction is included in the Computational Models of Cognition and Perception Series. A Bradford Book.


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Editorial Reviews

Review

"A broad, sweeping inquiry of what concepts are, what learning is, and how it can take place at all.... Induction is a deep synthesis of epistemology, evolution and computation. This path-breaking treatise will undoubtedly come to be recognized as a major step toward an interdisciplinary explanation of mentality" Douglas Hofstadter

About the Author

John Holland is Professor of Psychology at the University of Michigan, Ann Arbor.


Product Details

  • Paperback: 416 pages
  • Publisher: A Bradford Book; 1st MIT Press Ppbk Ed, 1989 edition (March 2, 1989)
  • Language: English
  • ISBN-10: 0262580969
  • ISBN-13: 978-0262580960
  • Product Dimensions: 8.7 x 5.8 x 1 inches
  • Shipping Weight: 1.5 pounds (View shipping rates and policies)
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Best Sellers Rank: #695,843 in Books (See Top 100 in Books)

More About the Author

Adapted from the Canadian Encyclopedia:

Paul R. Thagard, philosopher (b at Yorkton, Sask, 1950). Paul Thagard received a Bachelor of Arts from the University of Saskatchewan (1971), and completed degrees in philosophy at Cambridge University (1977) and the University of Toronto (1977). In 1985 he studied computer science at the University of Michigan (receiving an MSc), where he spent 8 years teaching philosophy at the Dearborn campus before accepting a position as a research psychologist at the University of Princeton (1986). Thagard later joined the University of Waterloo as a professor of philosophy, with a cross appointment to psychology and computer science, and director of the Cognitive Science Program. His considerable body of work (including many books and some 200 articles) has been profoundly influential to the study of human cognition in a wide range of practical and theoretical contexts.

Full article:
http://www.thecanadianencyclopedia.com/index.cfm?PgNm=TCE&Params=A1ARTA0010477

Web site:
http://watarts.uwaterloo.ca/~pthagard/Biographies/pault.html

 

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16 of 18 people found the following review helpful:
5.0 out of 5 stars A must for knowledge workers!, May 5, 2003
By 
S. van Diessen (The Hague, the Netherlands) - See all my reviews
This review is from: Induction: Processes of Inference, Learning, and Discovery (Paperback)
This book should be 'the bible' for everyone involved in knowledge management processes. Holland, as one of the complexity theory founders, decribes the essentials of how complex adaptive rules, in relation to the variability of the environment, determine knowledge dynamics and learning capabilities.

Key message of the book is the way that processes of induction, both cognitive and subcognitive, determine rule making, rule adaptation and environment modeling.

With this work Holland (et al.) was the first to close the gap between cognition, complex adaptive systems and knowledge processing. He also provides a sound computational base for the theories presented, opening possibilities for implementation of 'the induction theory' in real world applications.

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2 of 4 people found the following review helpful:
4.0 out of 5 stars science book, November 17, 2007
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This review is from: Induction: Processes of Inference, Learning, and Discovery (Paperback)
I wish I had read this book years ago. It help in my quest (research) to understand the Recognition process.
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Inside This Book (learn more)
First Sentence:
The mother of a four-year-old boy, observing that he has been unusually cranky and obdurate for several days, decides that he has entered a "phase". Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
unusualness heuristic, interdomain analogies, diachronic rules, abstract inferential rules, inductive adequacy, homomorphic model, alert timer, strength revision, effector rules, model transition function, plausible new rules, vision vector, default hierarchy, inhibitory rules, synchronic rules, default hierarchies, covariation detection, credit assignment algorithm, nondiagnostic information, donor concepts, inductive mechanisms, bucket brigade algorithm, pragmatic reasoning schemas, conceptual combination, source analog
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Affirming the Consequent, Denying the Antecedent, University of Michigan, Hong Kong, Default Condition, Ohio State University, World War, Employment Status
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