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 (999 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
Connectionist-Symbolic Integration
Language: en
Pages: 391
Authors: Ron Sun
Categories: Psychology
Type: BOOK - Published: 2013-04-15 - Publisher: Psychology Press

DOWNLOAD EBOOK

A variety of ideas, approaches, and techniques exist -- in terms of both architecture and learning -- and this abundance seems to lead to many exciting possibil
Handbook of Natural Language Processing
Language: en
Pages: 974
Authors: Robert Dale
Categories: Business & Economics
Type: BOOK - Published: 2000-07-25 - Publisher: CRC Press

DOWNLOAD EBOOK

This study explores the design and application of natural language text-based processing systems, based on generative linguistics, empirical copus analysis, and
Encyclopedia of Library and Information Sciences
Language: en
Pages: 5538
Authors: John D. McDonald
Categories: Computers
Type: BOOK - Published: 2017-03-15 - Publisher: CRC Press

DOWNLOAD EBOOK

The Encyclopedia of Library and Information Sciences, comprising of seven volumes, now in its fourth edition, compiles the contributions of major researchers an
Data Mining
Language: en
Pages: 485
Authors: John Wang
Categories: Computers
Type: BOOK - Published: 2003-01-01 - Publisher: IGI Global

DOWNLOAD EBOOK

Data Mining: Opportunities and Challenges presents an overview of the state of the art approaches in this new and multidisciplinary field of data mining. The pr