Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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... First Search Tree Algorithm : Depth - First Search 1. If the initial state is a goal state , quit and return success ... breadth - first search , where all of the tree that has so far been generated must be stored . • By chance ( or if ...
... First Search Tree Algorithm : Depth - First Search 1. If the initial state is a goal state , quit and return success ... breadth - first search , where all of the tree that has so far been generated must be stored . • By chance ( or if ...
Página 73
Elaine Rich. 3.3 Best - First Search Until now , we have really only discussed two systematic control strategies , breadth - first search and depth - first search ( of several varieties ) . In this section , we discuss a new method , best - ...
Elaine Rich. 3.3 Best - First Search Until now , we have really only discussed two systematic control strategies , breadth - first search and depth - first search ( of several varieties ) . In this section , we discuss a new method , best - ...
Página 323
... breadth - first search . Depth - first search was efficient in terms of space but required some cutoff depth in order to force backtracking when a solution was not found . Breadth ... first search , pruning any 12.5 . ITERATIVE DEEPENING 323.
... breadth - first search . Depth - first search was efficient in terms of space but required some cutoff depth in order to force backtracking when a solution was not found . Breadth ... first search , pruning any 12.5 . ITERATIVE DEEPENING 323.
Contenido
5 | 24 |
Heuristic Search Techniques | 63 |
Knowledge Representation Issues | 105 |
Derechos de autor | |
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Términos y frases comunes
Abbott agents algorithm answer apply approach ARMEMPTY assertions attributes axioms backpropagation backtracking backward belief best-first search breadth-first search Caesar called Chapter chess clauses complete concept conceptual dependency consider constraints contains contradiction corresponding define depth-first depth-first search described discussed domain fact frame function game tree goal grammar graph heuristic Horn clauses important inference inheritance input instance interpretation isa links John justification knowledge base knowledge representation labeled learning Marcus match minimax move MYCIN natural language node object ON(B operators output parsing particular path perceptron perform players possible preconditions predicate logic problem problem-solving procedure produce PROLOG properties represent result robot rules script Section semantic semantic net sentence shown in Figure simple slot solution solve specific step structure Suppose syntactic task techniques theorem things tree truth maintenance system understanding variables version space