Artificial Intelligence, Volumen1McGraw-Hill, 1983 - 436 páginas What is artificial intelligence?; Problem solving; Problems and problem spaces; Basic problem-solving methods; Game playing; Knowledge representation; Knowledge representation using predicate logic; Knowledge representation using other logics; Structured representation of knowledge; Advanced topics; Advanced problem-solving systems; Natural language understanding; Perception; Learning; Implementing A.lI. systems: languages and machines; Conclusion; References; Index. |
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Página ix
... Learning 361 11.1 What Is Learning ? 361 11.2 Random Learning and Neural Nets 363 11.3 Rote Learning 363 11.4 Learning by Parameter Adjustment 365 11.5 Learning in GPS 367 11.6 Concept Learning 368 11.7 Discovery as Learning : AM 375 11.8 ...
... Learning 361 11.1 What Is Learning ? 361 11.2 Random Learning and Neural Nets 363 11.3 Rote Learning 363 11.4 Learning by Parameter Adjustment 365 11.5 Learning in GPS 367 11.6 Concept Learning 368 11.7 Discovery as Learning : AM 375 11.8 ...
Página 363
Elaine Rich. 11.2 RANDOM LEARNING AND NEURAL NETS The analogy between human learning and machine learning is alluring . People learn by changing the structure of the neural network that makes up their brains . Why then should we not ...
Elaine Rich. 11.2 RANDOM LEARNING AND NEURAL NETS The analogy between human learning and machine learning is alluring . People learn by changing the structure of the neural network that makes up their brains . Why then should we not ...
Página 387
... learning procedure used this . o Matching . Concept learning exploits matching to detect similarities and differences between instances . • Hill climbing . Parameter adjustment and concept learning are both varieties of hill climbing ...
... learning procedure used this . o Matching . Concept learning exploits matching to detect similarities and differences between instances . • Hill climbing . Parameter adjustment and concept learning are both varieties of hill climbing ...
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A.I. programs algorithm answer applied approach appropriate arcs ARMEMPTY Artificial Intelligence backtracking best-first search branching factor breadth-first search Chapter chess clauses CLEAR(A complete Computer concept conceptual dependency consider constraints contains database described discussed domain example expert systems exploit explore fact frame game tree goal grammar graph heuristic heuristic function important input INTERLISP ISA links John knowledge representation labelings learning LISP machine Marcus match methods minimax move MYCIN natural language node objects ON(B operators parsing particular path performed possible preconditions predicate logic probabilistic problem problem-solving produce production system PROLOG propositional logic question reasoning representing knowledge rules Schank script search procedure search process Section semantic net sentence shown in Figure simple situation slots solution solve specific stack statements step strategy structure successors Suppose syntactic task techniques theorem things tion tree true variety