Parallel Distributed Processing, Volume 2: Explorations in the Microstructure of Cognition: Psychological and Biological Models

by David E. Rumelhart and James L. McClelland

Book Overview

What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human mind. They describe a new... This description may be from another edition of this product.

• Format: Paperback
• Language: English
• ISBN: 0262631105
• ISBN13: 9780262631105
• Release Date: July 1987
• Publisher: MIT Press
• Length: 632 Pages
• Weight: 2.15 lbs.
• Dimensions: 1.3" x 6.0" x 9.0"
• Age Range: 18 years and up
• Grade Range: Postsecondary and higher

Customer Reviews

Classic and Influential

This book establishes the foundation mathematics and definitions of what are now called "neural networks". In 1986 these guys (on DARPA grants) figured out the basics of what is (in my opinion) the most significant advance in artifical intelligence since the 1960s. The book is a bit dry, as a fully rigorous academic text usually is, but the results speak for themselves - the techniques and approaches described in this book are used all over in some of the most challenging areas of AI - character, speech, and face recognition, surveilance, applicant screening, and so on. Read it if you believe artifical intelligence is a bunch of hooey - I do, except this stuff.

A Historic Milestone: A book for AI and machine learning

Though I believe I am not the first person writing the book review of this historic book, I still feel honored to encourage the new readers to read this one of most important AI research book published in 1986. The book edited by Rumlhart and McClelland was well organized and well written, comprised of a series of independent and interesting topics in neural network researches given by the dedicated authors. The editors themselves are also reputated authors in the connectionist community. The most results in that book never appeared in the past publications and represented the high-quality papers in the state-of-the-art research at that time. Many papers in that book rank the top position of citation rate even today, e.g. the paper about error backpropagation due to Rumelhart, Hinton and Williams. I also got to point out that the importance of the book not only lies in its scientific contribution, but also its philosophical meaning in the AI research (which is somehow influenced by the book 'Perceptrons' by Minsky and Pappert). The successful research results in that book showed people of the potential and new prospect of neural networks in different perspectives. From then on the second connectionist revolution has sprang and lasted today. Nowadays, people still can feel its leading influence by reading it. Upon reading the book again and again, you will always feel inspired at another new way (that is the value of a book!). Try it immediately. In a word without exaggeration, the importance of this book to connectionist and AI researchers is like the Bible to Christians. Read it, enjoy it, once and again.