Artificial IntelligenceThe breadth of A. I. is explored and explained in this best selling text. Assuming no prior knowledge,it covers topics like neural networks and robotics. This text explores the range of problems which have been and remain to be solved using A. I. tools and techniques. The second half of this text is an excellent reference. |
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Página 504
The weights connected to the output units can be adjusted in order to reduce
those errors . We can then use the error estimates of the output units to derive
error estimates for the units in the hidden layers . Finally , errors are propagated
back ...
The weights connected to the output units can be adjusted in order to reduce
those errors . We can then use the error estimates of the output units to derive
error estimates for the units in the hidden layers . Finally , errors are propagated
back ...
Página 518
State Units 000 OOOTI Plan Output Units Units Hidden Units Figure 18 . 22 : A
Jordan Network of muscles ) , but we need more than a single output vector . We
need a series of output vectors : first move the muscles this way , then this way ...
State Units 000 OOOTI Plan Output Units Units Hidden Units Figure 18 . 22 : A
Jordan Network of muscles ) , but we need more than a single output vector . We
need a series of output vectors : first move the muscles this way , then this way ...
Página 521
How can we accomplish the same task with neuronlike units ? The localist
approach is to maintain an array of sixty - four units , one unit for every possible
location ( see Figure 18 . 24 ) . A more efficient approach would be to use a group
of ...
How can we accomplish the same task with neuronlike units ? The localist
approach is to maintain an array of sixty - four units , one unit for every possible
location ( see Figure 18 . 24 ) . A more efficient approach would be to use a group
of ...
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Contenido
Problems Problem Spaces and Search | 29 |
7 | 61 |
Knowledge Representation Issues | 105 |
Derechos de autor | |
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Términos y frases comunes
active addition agents algorithm allow answer apply approach assertions becomes belief build called Chapter choose clauses combined complete concept consider consistent constraints contains corresponding define dependency described discussed domain elements example fact Figure function given goal heuristic important initial input instance interpretation John kinds knowledge knowledge base labeled language learning logic look match meaning methods move natural necessary node object occur operators output particular path perform position possible predicate present problem procedure produce properties question reasoning relation represent representation result robot rules semantic sentence shown in Figure shows simple single situation slot solution solve space specific statements step stored structure Suppose task techniques things tree true understanding units usually variables weights
Información bibliográfica
| Título | Artificial Intelligence Artificial Intelligence Series Mac Graw-Hill series in artificial inteligence |
| Autores | Elaine Rich, Kevin Knight, Knight Kevin |
| Edición | 2, ilustrada |
| Editor | McGraw-Hill, 1991 |
| ISBN | 0070522634, 9780070522633 |
| Largo | 621 páginas |
| Exportar cita | BiBTeX EndNote RefMan |