경문사

쇼핑몰 >  수입도서 >  Engineering >  Computer/Electrical and Eletronics

Parallel Distributed Processing, Vol. 2(1987)  무료배송

 
지은이 : Rumelhart
출판사 : MIT
판수 : 1 edition
페이지수 : 632 pages
ISBN : 0262631105
예상출고일 : 입금확인후 2일 이내
주문수량 :
도서가격 : 53,900원 ( 무료배송 )
적립금 : 1,617 Point
     

 
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 theory of cognition called connectionism that is challenging the idea of symbolic computation that has traditionally been at the center of debate in theoretical discussions about the mind. The authors' theory assumes the mind is composed of a great number of elementary units connected in a neural network. Mental processes are interactions between these units which excite and inhibit each other in parallel rather than sequential operations. In this context, knowledge can no longer be thought of as stored in localized structures; instead, it consists of the connections between pairs of units that are distributed throughout the network. Volume 1 lays the foundations of this exciting theory of parallel distributed processing, while Volume 2 applies it to a number of specific issues in cognitive science and neuroscience, with chapters describing models of aspects of perception, memory, language, and thought. David E. Rumelhart is Professor of Psychology at the University of California, San Diego. James L. McClelland is Professor of Psychology at Carnegie-Mellon University. A Bradford Book.
James L. McClelland is Professor of Psychology and Director of the Center for Mind, Brain, and Computation at Stanford University. He is the coauthor of Parallel Distributed Processing (1986) and Semantic Cognition (2004), both published by the MIT Press.

David E. Rumelhart is Professor of Psychology at the University of California, San Diego. With James McClelland, he was awarded the 2002 University of Louisville Grawemeyer Award for Psychology for his work in the field of cognitive neuroscience on a cognitive framework called parallel distributed processing and the concept of connectionism.
IV PSYCHOLOGICAL PROCESSES

14 Schemata and Sequential Thought Processes in PDP Models

15 Interactive Processes in Speech Perception: The TRACE Model

16 The Programmable Blackboard Model of Reading

17 A Distributed Model of Human Learning and Memory

18 On Learning the Past Tenses of English Verbs

19 Mechanisms of Sentence Processing: Assigning Roles to Constituents

V BIOLOGICAL MECHANISMS

20 Certain Aspects of the Anatomy and Physiology of the Cerebral Cortex

21 Open Questions About Computation in Cerebral Cortex

22 Neural and Conceptual Interpretation of PDP Models

23 Biologically Plausible Models of Place Recognition and Goal Location

24 State-Dependent Factors Influencing Neural Plasticity: A Partial Account of the Critical Period

25 Amnesia and Distributed Memory

VI CONCLUSION

26 Reflections on Cognition and Parallel Distributed Processing

"Rumelhart and McClelland propose that what is stored in memory is not specific facts or events, but rather the relationships between the various aspects of those facts or events as they are encoded in groupings of neuronal cells or patterns of cell activity." Daniel Coleman, The New York Times




"[This is] a comprehensive compilation of neural network research and development. There are algorithms you can use to explore various methods in the field. If you want information on neural network technology in book form, this is the set to own." Artificial Intelligence Special Interest Group Newsletter

"
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. "

"


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. "

   
 
   
 
책 오류요
beer의 알기쉬운 재료역...
올림피아드 기출 문제집...
Parallel Distribut...
Explorations in PD...
Space-Time Block C...
Parallel Distribut...