Artificial Intelligence |
Dentro del libro
Resultados 1-3 de 68
Página 504
The network adjusts its weights each time it sees an input - output pair . Each pair
requires two stages : a forward pass and a backward pass . The forward pass
involves presenting a sample input to the network and letting activations flow until
...
The network adjusts its weights each time it sees an input - output pair . Each pair
requires two stages : a forward pass and a backward pass . The forward pass
involves presenting a sample input to the network and letting activations flow until
...
Página 511
Given a set of input data , the network is allowed to play with it to try to discover
regularities and relationships between the different parts of the input . Learning is
often made possible through some notion of which features in the input set are ...
Given a set of input data , the network is allowed to play with it to try to discover
regularities and relationships between the different parts of the input . Learning is
often made possible through some notion of which features in the input set are ...
Página 513
Algorithm : Competitive Learning Given : A network consisting of n binary -
valued input units directly connected to any ... Produce : A set of weights such
that the output units become active according to some natural division of the
inputs . 1 .
Algorithm : Competitive Learning Given : A network consisting of n binary -
valued input units directly connected to any ... Produce : A set of weights such
that the output units become active according to some natural division of the
inputs . 1 .
Comentarios de la gente - Escribir un comentario
No encontramos ningún comentario en los lugares habituales.
Contenido
What Is Artificial Intelligence? | 3 |
Problems Problem Spaces and Search | 29 |
Heuristic Search Techniques | 63 |
Derechos de autor | |
Otras 21 secciones no mostradas
Otras ediciones - Ver todas
Términos y frases comunes
active addition agents algorithm allow answer apply approach assertions becomes belief build called Chapter 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