Fluid Concepts and Creative Analogies: Computer Models Of The Fundamental Mechanisms Of Thought Paperback – March 22, 1996

When I first read this book years ago, I found it very intuitive and exciting to look at the problems in this new way. It definitely makes a clear distinction between "expert systems" and proper intelligence. I recently went back and started reading it again. I'm still amazed by the false sense of simplicity of the problems Hofstaedter tries to solve and how complex they actually are. I wonder if they are not complete in some sense anyhow.It's great fun reading the book and following the train of thoughts is enjoyable and simple enough ... at least for somebody with a basic understanding in maths and maybe some AI knowledge. So if you started to read Gödel, Escher, Bach: An Eternal Golden Braid but never finished it, this is a much easier and more pragmatic read than Hofstaedter's more generic book.

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.

I bought this book after reading Melanie Mitchell's book Complexity: A Guided Tour. I wanted to read more about her Copycat project, and Fluid Concepts has a few chapters on that.This book is really a collection of articles about different projects attempting to model the way people think. It's not about artificial intelligence the way most people think of it nowadays (pattern matching), but more about how people relate ideas to each other. You might think it would be outdated, but I get the sense that most AI researchers have not pursued this way of thinking, instead focusing on neural networks (machine learning).The articles are collected with (some) hindsight and editing to prevent too much repetition. That said, it's still a bit repetitive in many places. However, that's forgivable because the ideas are so revolutionary that some repetition is desirable.Hofstadter's ideas seem right on to me. If you want to learn about those ideas, this book is more accessible than Goedel, Escher, Bach, though if you get interested in Hofstadter you should definitely read GEB.

No problems, good experience.

As I am full fling into developing a new parallel computer architecture, this book is providing me with loads of insights. The orientation of the book towards understanding on an abstract level is exactly what I was looking for. I love it.

Loved it! Fascinating read on cognitive science. A little out of date, but well worth the read.

An articulate discussion of a set of important experiments in cognitive science.

Explores the broad strokes of a decade's worth of research by one of the most eloquent and interesting cognitive scientists working. I personally would have been happier to delve deeper into the specifics of the projects--appending some of the papers in question would be a nice touch in a re-issue.