Analogies Books

Fluid Concepts And Creative Analogies: Computer Models Of The Fundamental Mechanisms Of Thought

Douglas R. Hofstadter

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Customer Reviews:
Total reviews: 14 Average rating: 4.0 of 5

Wonderful but quite dry in parts 5 out of 5 stars.
18 of 18 people found this review helpful.

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.

Editorial Review:

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.

The Subtlety of Sameness: A Theory and Computer Model of Analogy-Making

Robert M. French

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Editorial Review:

Foreword by Daniel Dennett

While it is fashionable today to dismiss the "bad old days" of artificial intelligence and rave about emergent self-organizing systems, Robert French has created a model of human analogy-making that attempts to bridge the gap between classical top-down AI and more recent bottom-up approaches.

The research described in this book is based on the premise that human analogy-making is an extension of our constant background process of perceiving—in other words, that analogy-making and the perception of sameness are two sides of the same coin. At the heart of the author's theory and computer model of analogy-making is the idea that the building-up and the manipulation of representations are inseparable aspects of mental functioning, in contrast to traditional AI models of high-level cognitive processes, which have almost always depended on a clean separation.

A computer program called Tabletop forms analogies in a microdomain consisting of everyday objects on a table set for a meal. The theory and the program rely on the idea that myriad stochastic choices made on the microlevel can add up to statistical robustness on a macrolevel. To illustrate this, French includes the results of thousands of runs of his program on several dozen interrelated analogy problems in the Tabletop microworld.

French's work is exciting not only because it reveals analogy-making to be an extension of our complex and subtle ability to perceive sameness but also because it offers a computational model of mechanisms underlying these processes. This model makes significant strides in putting into practice microlevel stochastic processing, distributed processing, simulated parallelism, and the integration of representation-building and representation-processing.

A Bradford Book