Active learning of actions based on support vector machines

Francisco Ruiz, Albert Samà, Núria Agell

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

Resum

Action learning is a methodology based on a machine learning system that makes it possible to select a suitable action or sequence of actions given a state. The main drawback of this methodology is the difficulty of assigning a class to the state-action pair to be included in the training set. This paper proposes an active learning methodology in the learning phase of an action learning process. With the help of an artificial example, the active methodology is compared with a passive methodology consisting of randomly selecting the training set from the pool of unlabelled patterns.

Idioma originalAnglès
Títol de la publicacióArtificial Intelligence Research and Development. Proceedings of the 15th International Conference of the Catalan Association for Artificial Intelligence
EditorIOS Press
Pàgines37-46
Nombre de pàgines10
ISBN (imprès)9781614991380
DOIs
Estat de la publicacióPublicada - 2012
Publicat externament

Sèrie de publicacions

NomFrontiers in Artificial Intelligence and Applications
Volum248
ISSN (imprès)0922-6389

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