@incollection{iiasa13612,
          volume = {i},
       booktitle = {Proceedings. The Seventh IEEE Conference on Artificial Intelligence Application},
         address = {Piscataway, NJ, United States},
           title = {ALEX: automatic learning in expert systems},
       publisher = {IEEE},
             doi = {doi:10.1109/CAIA.1991.120846},
           pages = {59--62},
            year = {1991},
             url = {http://dx.doi.org/10.1109/CAIA.1991.120846},
        abstract = {An environment for automatic learning (ALEX) has been designed and implemented in a modular fashion. The system consists of an example generation module (i.e., tutor software system representing the application domain); the learning subsystem; an analysis component; and the user interface and control structure integrating these components. As the core of the learning subsystem the incremental learning algorithm ID-H has been developed, based on the incremental application of hybrid clustering. To improve the overall performance of the learning environment, a feedback loop between the results of a learning step and the input of the next learning step has been introduced. The learning environment can automatically direct its learning strategy according to its assessment of its performance},
          author = {Winkelbauer, L. and Fedra, K.}
}