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The interdisciplinary field of cognitive science brings together elements of cognitive psychology, mathematics, perception, linguistics, and artificial intelligence. Cognitive Science provides a unified and comprehensive look at the field, from foundations to applications. The author 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.
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.
Explicit Symbol Based Learning Models.
Connectionist Networks: History, The Perception, and Backpropagation.
Competitive, Reinforcement, and Attractor Learning Models.
Language Representation and Processing.
Pragmatics and Discourse.
Building Cognitive Representations in PROLOG:
PROLOG as Representation and Language.
Creating Meta-Interpreters in PROLOG.
Cognitive Science: Problems and Promise.