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The Pattern Recognition Basis of Artificial Intelligence (Practitioners), by Donald Tveter
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This book takes the viewpoint that plain symbol processing techniques have little hope of reproducing the depth and breadth of capabilities found in human beings. The book introduces new foundational principles to AI: connectionist/neural networking methods, case based and memory based methods and picture processing.
The book looks at methods of AI as different ways of doing pattern recognition. One way to do pattern recognition is to compare a problem to stored cases. At the other end of the spectrum, Classical Symbol Processing AI compresses cases down to a small set of rules and then works only with this condensed knowledge. In between these two extremes are neural networks, especially backprop type networks. As much as possible the book compares these three basic methods using actual AI programs.
The structure of the book starts at the bottom of human abilities with vision and other simple pattern recognition abilities and moves on to the higher levels of problem solving and game playing and finally to the level of natural language and understanding of the world. At the higher levels more complex computer architectures are needed that include methods for structuring thoughts.
The book is organized in a manner in which the reader will get an intuitive feeling for the principles of AI. Throughout the book applications of basic principles are demonstrated by examining some classic AI programs in detail. The book can serve as a text for juniors, seniors and first year graduate students in Computer Science or Psychology and includes sample problems and data for exercises and a list of frequently asked questions.
- Sales Rank: #4649823 in Books
- Brand: Brand: Wiley-IEEE Computer Society Pr
- Published on: 1998-03-13
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.45" h x .82" w x 7.50" l, 1.50 pounds
- Binding: Paperback
- 388 pages
- Used Book in Good Condition
Most helpful customer reviews
0 of 0 people found the following review helpful.
Easy to read book
By Ricardo Land Rodrigues
If you want an start book to read about pattern recognition it is your book. Easy to read with lots of information. Good begining book
4 of 4 people found the following review helpful.
Somewhere between a general audience book and a text
By Todd Ebert
I found this book quite interesting due to the way it was structured (from low-level tasks requiring pattern recognition and neural networks to high-level tasks such as game playing and natural language), and due to the author's use of pattern recogniton as a theme for intelligence. In many sections towards the end of each chapter, he also hints at how it may be possible to merge the connectionist and symbolic approaches to AI. For example, with respect to game playing, he discusses possible ways to include backpropagation as tool for evolving a good game evaluation function for backgammon. I also found his intuitive discussions on neural networks (chapters 2 and 3) quite engaging, with an emphasis on possible applications more so than a rigorous mathematical treatment. One main problem I have with the book, however, is its tendency to oversimplify or omit important aspects of the theory. For example, no where does he mention Bayesian classification methods in the pattern recognition chapters. And in general he does not seem to acknowledge the importance of probability in AI. I plan to use the text in a 5 week summer course in AI, because I believe that, with such short time, a terse but engaging book along with good lecture notes seems most appropriate. However, had the couse been 10 or 16 weeks, I would have opted for a more standard text that has 3x as many pages and definitions (e.g. Nilsson's good book). In closing, I recommend this book to anyone who is interested in learning some AI , but does not want to be overburdened with math, or to an expert who prefers to browse the discussions to gain a possibly new perspective on the material.
3 of 3 people found the following review helpful.
The book provides an alternative approach to learning AI.
By Amit Konar
This is an interesting book that introduces AI from a pattern recognition point of view.The author attempted and solved many complex problems by neurocomputing approach. He thus emphasizes the need for neural approach in Artificial Intelligence. He however did not eliminate the scope of all conventional approaches. Some comparative study of the conventioanl and neural algorithms are apparent from the text. The writing style is beautiful. Mature readers will find the book like a novel. I strongly recommend the book for those who want to see the contrast between the "symbol processing AI" and "the neural AI".
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