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.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com