Computational Architectures Integrating Neural and Symbolic Processes

Computational Architectures Integrating Neural and Symbolic Processes
Author :
Publisher : Springer
Total Pages : 490
Release :
ISBN-10 : 9780585295992
ISBN-13 : 0585295999
Rating : 4/5 (92 Downloads)

Book Synopsis Computational Architectures Integrating Neural and Symbolic Processes by : Ron Sun

Download or read book Computational Architectures Integrating Neural and Symbolic Processes written by Ron Sun and published by Springer. This book was released on 2007-08-19 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art focuses on a currently emerging body of research. With the reemergence of neural networks in the 1980s with their emphasis on overcoming some of the limitations of symbolic AI, there is clearly a need to support some form of high-level symbolic processing in connectionist networks. As argued by many researchers, on both the symbolic AI and connectionist sides, many cognitive tasks, e.g. language understanding and common sense reasoning, seem to require high-level symbolic capabilities. How these capabilities are realized in connectionist networks is a difficult question and it constitutes the focus of this book. Computational Architectures Integrating Neural and Symbolic Processes addresses the underlying architectural aspects of the integration of neural and symbolic processes. In order to provide a basis for a deeper understanding of existing divergent approaches and provide insight for further developments in this field, this book presents: (1) an examination of specific architectures (grouped together according to their approaches), their strengths and weaknesses, why they work, and what they predict, and (2) a critique/comparison of these approaches. Computational Architectures Integrating Neural and Symbolic Processes is of interest to researchers, graduate students, and interested laymen, in areas such as cognitive science, artificial intelligence, computer science, cognitive psychology, and neurocomputing, in keeping up-to-date with the newest research trends. It is a comprehensive, in-depth introduction to this new emerging field.


Computational Architectures Integrating Neural and Symbolic Processes Related Books

Computational Architectures Integrating Neural and Symbolic Processes
Language: en
Pages: 490
Authors: Ron Sun
Categories: Computers
Type: BOOK - Published: 2007-08-19 - Publisher: Springer

DOWNLOAD EBOOK

Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art focuses on a currently emerging body of research. W
An Introduction to Neural Networks
Language: en
Pages: 234
Authors: Kevin Gurney
Categories: Computers
Type: BOOK - Published: 2018-10-08 - Publisher: CRC Press

DOWNLOAD EBOOK

Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of th
Data Mining
Language: en
Pages: 496
Authors: John Wang
Categories: Computers
Type: BOOK - Published: 2003-01-01 - Publisher: IGI Global

DOWNLOAD EBOOK

"An overview of the multidisciplinary field of data mining, this book focuses specifically on new methodologies and case studies. Included are case studies writ
Encyclopedia of Library and Information Science, Second Edition -
Language: en
Pages: 922
Authors: Miriam Drake
Categories: Language Arts & Disciplines
Type: BOOK - Published: 2003-05-20 - Publisher: CRC Press

DOWNLOAD EBOOK

A revitalized version of the popular classic, the Encyclopedia of Library and Information Science, Second Edition targets new and dynamic movements in the distr
Agents in the Long Game of AI
Language: en
Pages: 337
Authors: Marjorie Mcshane
Categories: Computers
Type: BOOK - Published: 2024-09-03 - Publisher: MIT Press

DOWNLOAD EBOOK

A novel approach to hybrid AI aimed at developing trustworthy agent collaborators. The vast majority of current AI relies wholly on machine learning (ML). Howev