Artificial IntelligenceMcGraw-Hill, 1991 - 621 páginas |
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Elaine Rich. Move object Move robot Clear object Get object on object Get arm empty Be holding object Push Carry Walk Pickup Putdown Place * * * * * * * * Figure 3.16 : A Difference Table A Start B Push C D Goal Figure 3.17 : The ...
Elaine Rich. Move object Move robot Clear object Get object on object Get arm empty Be holding object Push Carry Walk Pickup Putdown Place * * * * * * * * Figure 3.16 : A Difference Table A Start B Push C D Goal Figure 3.17 : The ...
Página 563
... object , determining the two - dimensional extent of the object depicted . 3. Pattern Recognition - For single - object images , classifying the object into a cat- egory drawn from a finite set of possibilities . 4. Image Understanding ...
... object , determining the two - dimensional extent of the object depicted . 3. Pattern Recognition - For single - object images , classifying the object into a cat- egory drawn from a finite set of possibilities . 4. Image Understanding ...
Página 564
... objects , and some objects may partially occlude others , as we saw earlier in Figure 14.8 . • The value of a single pixel is affected by many different phenomena , including the color of the object , the source of the light , the angle ...
... objects , and some objects may partially occlude others , as we saw earlier in Figure 14.8 . • The value of a single pixel is affected by many different phenomena , including the color of the object , the source of the light , the angle ...
Contenido
5 | 24 |
Heuristic Search Techniques | 63 |
Knowledge Representation Issues | 105 |
Derechos de autor | |
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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