
Cognitive Science
The Science of Intelligent Systems
Academic Press
Published on 6. July 1994
Book
Hardback
666 pages
978-0-12-459570-5 (ISBN)
Description
The interdisciplinary field of cognitive science brings together elements of cognitive psychology, mathematics, perception, linguistics, and artificial intelligence. Given this breadth, textbooks have had difficulty providing balanced coverage-most resort to disjointed edited treatises that prove difficult to use.Cognitive Science provides a unified and comprehensive look at the field, from foundations to applications. Luger explores the logical and philosophical bases of cognitive science with multiple models of intelligence, including neural networks and connectionism. Practical programming examples are included along with an introduction to PROLOG.
More details
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
AUDIENCE: Upper-division students in cognitive science.
Dimensions
Height: 229 mm
Width: 152 mm
Weight
1070 gr
ISBN-13
978-0-12-459570-5 (9780124595705)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Author
University of New Mexico, Albuquerque, U.S.A.
University of New Mexico, Albuquerque, U.S.A.
University of New Mexico, Albuquerque, U.S.A.
University of New Mexico, Albuquerque, U.S.A.
Content
Introduction to Cognitive Science:
Intelligence and the Roots of Cognitive Science.
Vocabularies for Describing Intelligence.
Representation Schemes.
Constraining the Architecture of Minds.
Natural Intelligence: Brain Function.
Symbol Based Representation and Search:
Network and Structured Representation Schemes.
Logic Based Representation and Reasoning.
Search Strategies for Weak Method Problem Solving.
Using Knowledge and Strong Method Problem Solving.
Machine Learning:
Explicit Symbol Based Learning Models.
Connectionist Networks: History, The Perception, and Backpropagation.
Competitive, Reinforcement, and Attractor Learning Models.
Language:
Language Representation and Processing.
Pragmatics and Discourse.
Building Cognitive Representations in PROLOG:
PROLOG as Representation and Language.
Creating Meta-Interpreters in PROLOG.
Epilogue:
Cognitive Science: Problems and Promise.
References.
Index.
Intelligence and the Roots of Cognitive Science.
Vocabularies for Describing Intelligence.
Representation Schemes.
Constraining the Architecture of Minds.
Natural Intelligence: Brain Function.
Symbol Based Representation and Search:
Network and Structured Representation Schemes.
Logic Based Representation and Reasoning.
Search Strategies for Weak Method Problem Solving.
Using Knowledge and Strong Method Problem Solving.
Machine Learning:
Explicit Symbol Based Learning Models.
Connectionist Networks: History, The Perception, and Backpropagation.
Competitive, Reinforcement, and Attractor Learning Models.
Language:
Language Representation and Processing.
Pragmatics and Discourse.
Building Cognitive Representations in PROLOG:
PROLOG as Representation and Language.
Creating Meta-Interpreters in PROLOG.
Epilogue:
Cognitive Science: Problems and Promise.
References.
Index.