Teaching Randomized Learners Authors: Frank J. Balbach and Thomas Zeugmann Source: Learning Theory, 19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 2006, Proceedings, (Gabor Lugosi and Hans Ulrich Simon, Eds.), Lecture Notes in Artificial Intelligence 4005, pp. 229 - 243, Springer 2006. Abstract. The present paper introduces a new model for teaching randomized learners. Our new model, though based on the classical teaching dimension model, allows to study the influence of various parameters such as the learner's memory size, its ability to provide or to not provide feedback, and the influence of the order in which examples are presented. Furthermore, within the new model it is possible to investigate new aspects of teaching like teaching from positive data only or teaching with inconsistent teachers. Furthermore, we provide characterization theorems for teachability from positive data for both ordinary teachers and inconsistent teachers with and without feedback. ©Copyright 2006, Springer