Artificial Intelligence: Theory and Practice
Benjamin/Cummings Publishing Company, 1995 - Computers - 563 pages
This book provides a detailed understanding of the broad issues in artificial intelligence and a survey of current AI technology. The author delivers broad coverage of innovative representational techniques, including neural networks, image processing and probabilistic reasoning, alongside the traditional methods of symbolic reasoning. The work is intended for students in artificial intelligence, researchers and LISP programmers.
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abstract abstract data type algorithm apply arguments assigned associated axioms basis functions believe(a best-first search boolean functions breadth-first breadth-first search called chapter Common Lisp concept configuration conjunction consider consistent corresponding data type database decision tree defined defun depth-first search described determine discrimination tree disjunction environment eval evaluation function expression formula genetic algorithms given goal gradient graph hypothesis space implementation indicates initial input instance interpretation involving iterative labeled lambda language logic mapcar match method objects operators output pairs parameters particular perceptron perform possible problem propositional propositional logic quantified reasoning recursive represent representation result returns robot rules of inference search space semantics sentence sequence setq shown in Figure situation calculus specified step structure subset symbol techniques theorem theory tion training examples True variables weights
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