Cognitive science: the science of intelligent systems
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.
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algorithm Allen Newell analysis approach architecture artificial intelligence backpropagation behavior best-first search brain breadth-first breadth-first search Chapter cognitive science cognitive scientists complex concept conceptual dependency connectionist constraints context defined depth-first depth-first search describe discussion domain example Figure formal frame function goal graph Hebbian learning heuristic human hypothesis important inference input instance intelligent systems interpretation knowledge language layer learning linguistic logic mapping match mathematical meaning memory method neural neurons Newell and Simon node noun objects output path pattern perceptron physical physical symbol system predicate calculus present problem solving procedure processing production rules production system PROLOG properties propositional psycholinguistics reasoning referred relationships represent representational schemes Section semantic sentence situation solution space speaker specific stimulus structure symbol based symbol system task theory tion Turing machine understanding values variable vector weight words