Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Página xii
... Learning 445 447 17.1 What Is Learning ? 447 17.2 Rote Learning 448 17.3 Learning by Taking Advice 450 17.4 Learning in Problem Solving . 452 17.5 Learning from Examples : Induction 457 17.6 Explanation - Based Learning 471 17.7 ...
... Learning 445 447 17.1 What Is Learning ? 447 17.2 Rote Learning 448 17.3 Learning by Taking Advice 450 17.4 Learning in Problem Solving . 452 17.5 Learning from Examples : Induction 457 17.6 Explanation - Based Learning 471 17.7 ...
Página 448
... learning . However , many Al programs are able to improve their performance substantially through rote - learning techniques , and we will look at one example in depth , the checker - playing program of Samuel ... LEARNING Rote Learning.
... learning . However , many Al programs are able to improve their performance substantially through rote - learning techniques , and we will look at one example in depth , the checker - playing program of Samuel ... LEARNING Rote Learning.
Página 482
... Learning Theory Like many other AI problems , learning has attracted the attention of mathematicians and theoretical computer scientists . Inductive learning in particular has received con- siderable attention . Valiant [ 1984 ] ...
... Learning Theory Like many other AI problems , learning has attracted the attention of mathematicians and theoretical computer scientists . Inductive learning in particular has received con- siderable attention . Valiant [ 1984 ] ...
Contenido
Weak SlotandFiller Structures | 9 |
6 | 24 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
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Abbott algorithm answer apply approach Artificial Intelligence assertions attributes axioms backpropagation backtracking backward backward reasoning belief best-first search breadth-first search Cabot Caesar Chapter clauses concept consider constraints contains contexts contradiction corresponding define depth-first depth-first search described discussed domain example explicitly fact given goal graph heuristic heuristic function Horn clauses important inference inheritance input instance interpretation justification knowledge base knowledge representation labeled learning logical assertions Marcus match move MYCIN node nonmonotonic reasoning object operators particular path perceptron possible preconditions predicate logic problem problem-solving procedure produce production system PROLOG propagation propositional logic question represent resolution result robot rules Section semantic semantic net sentence shown in Figure simple slot solution solve space specific statements step strategy structure Suppose suspect syntactic task techniques theorem things tree true truth maintenance system variables wff's