Cognitive Science
The Science of Intelligent Systems
- 1st Edition - May 25, 1994
- Latest edition
- Authors: George F. Luger, Peder Johnson, Carl Stern, Jean E. Newman, Ronald Yeo
- Language: English
- Hardback ISBN:9 7 8 - 0 - 1 2 - 4 5 9 5 7 0 - 5
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 9 2 4 3 7 - 3
The interdisciplinary field of cognitive science brings together elements of cognitive psychology, mathematics, perception, linguistics, and artificial intelligence. Given this… Read more
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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.
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.
AUDIENCE: Upper-division students in cognitive science.
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.
- Edition: 1
- Latest edition
- Published: May 25, 1994
- Language: English
GL
George F. Luger
Affiliations and expertise
University of New Mexico, Albuquerque, U.S.A.CS
Carl Stern
Affiliations and expertise
University of New Mexico, Albuquerque, U.S.A.JN
Jean E. Newman
Affiliations and expertise
University of New Mexico, Albuquerque, U.S.A.RY
Ronald Yeo
Affiliations and expertise
University of New Mexico, Albuquerque, U.S.A.