- Paperback: 528 pages
- Publisher: Basic Books (Mar 1 1996)
- Language: English
- ISBN-10: 0465024750
- ISBN-13: 978-0465024759
- Product Dimensions: 25 x 18.5 x 3 cm
- Shipping Weight: 939 g
- Average Customer Review: 3.9 out of 5 stars See all reviews (9 customer reviews)
- Amazon Bestsellers Rank: #241,118 in Books (See Top 100 in Books)
- See Complete Table of Contents
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Product Details |
Product Description
From Amazon
Douglas Hofstadter, best known for his masterpiece Godel, Escher, Bach: An Eternal Golden Braid, tackles the subject of artificial intelligence and machine learning in his thought-provoking work Fluid Concepts and Creative Analogies, written in conjunction with the Fluid Analogies Research Group at the University of Michigan. Driven to discover whether computers can be made to "think" like humans, Hofstadter and his colleagues created a variety of computer programs that extrapolate sequences, apply pattern-matching strategies, make analogies, and even act "creative." As always, Hofstadter's work requires devotion on the part of the reader, but rewards him with fascinating insights into the nature of both human and machine intelligence.
Book Description
Readers of earlier works by Douglas Hofstadter will find this book a natural extension of his style and his ideas about creativity and analogy; in addition, psychologists, philosophers, and artificial-intelligence researchers will find in this elaborate web of ingenious ideas a deep and challenging new view of mind.
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Most helpful customer reviews
1 of 1 people found the following review helpful
3.0 out of 5 stars
Too distant from my usual routes ...,
By Massimiliano Celaschi (Graffignano, Viterbo Italy) - See all my reviews
This review is from: Fluid Concepts and Creative Analogies: Computer Models Of the Fundamental Mechanisms Of Thought (Paperback)
Many books by D. Hofstadter are at the top standings of my personal parade, but in reading this book I found myself very likely too distant from my usual interests and preferred styles. The initial part is very interesting, but when the author carries on detailed descriptions about programs' features in conversational shape, I have been quickly bored, and I have given up attentive reading turning to an eagle eye approach. I would have been by far more comfortable with a more formal explanation, because, once I make the effort to follow the thourough description of what and how a program does, it is more convenient to study its algorithms.So, the book is surely very pleasing for people professionally involved in semantics, but I am not confident in its general interest.
1 of 1 people found the following review helpful
4.0 out of 5 stars
Thought-provoking account of a diverse field of research,
By
This review is from: Fluid Concepts and Creative Analogies: Computer Models Of the Fundamental Mechanisms Of Thought (Paperback)
Douglas Hofstadter is best known for his seminal work 'Godel, Escher, Bach' (1981), but not much was known about the work he carried out at the University of Indiana. This work collects a number of research papers from the 80s, thus offering a glimpse into the continuation of the work that was carried out with the help of the 'fluid concepts'-group. Hofstadter writes well, which means that the accounts of the projects that were undertaken are exciting, thought-provoking, and intruiging. I'm not entirely happy about the theoretical background to some of the work, maybe Hofstadter tries too deliberately to maintain things at a simple level. Still, if you're at all interested in the state of the art in AI research, this is a book you may not want to miss.
5.0 out of 5 stars
Wonderful but quite dry in parts,
By
This review is from: Fluid Concepts and Creative Analogies: Computer Models Of the Fundamental Mechanisms Of Thought (Paperback)
This book is, as others have commented, different from DH's other more entertaining books. It is a serious attempt to discuss the real issues and difficulties with AI research. There is a lot of quite dry material and in places it is repetitive. It provides terrific insight into the problem of imitating human thinking at a deep level, and I found it very rewarding. It was also very interesting to follow the threads of how he went about doing research, and what he thought of other AI research. His views of various flavours of AI research were very instructive and inightful I thought. In summary a good book, but this is not (high quality) brain candy like Godel Escher Bach etc.
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