@inproceedings{592bd872c0014294a5c0d82067bf9055,
title = "Active learning of actions based on support vector machines",
abstract = "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.",
keywords = "Action learning, Active learning, SVM",
author = "Francisco Ruiz and Albert Sam{\`a} and N. Agell",
year = "2012",
doi = "10.3233/978-1-61499-139-7-37",
language = "English",
isbn = "9781614991380",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press",
pages = "37--46",
booktitle = "Artificial Intelligence Research and Development. Proceedings of the 15th International Conference of the Catalan Association for Artificial Intelligence",
address = "Netherlands",
}