Using learning automata to model a student-classroom interaction in a tutorial-like system
Khaled Hashem, B. John Oommen · 2007
Almost all of the learning paradigms used in machine learning, learning automata (LA), and learning theory, in general, use the philosophy of a student (learning mechanism) attempting to learn from a teacher. This paradigm has been generalized in a myriad of ways including the scenario when there are multiple teachers or a hierarchy of mechanisms which collectively achieve the learning. In this paper, we consider a departure from this paradigm by allowing the student to be a member of a classroom of students, where, for the most part, we permit each member of the classroom to not only learn from the teacher(s) but also to "extract" information from any of his colleague students. This paper deals with the issues concerning the modeling, decision making process and testing of such a scenario within the LA context. The main result that we show is that a weak learner can actually benefit from this capability of utilizing the information that the gets from a superior colleague - if this information transfer is done appropriately.