Mutual learning using nonlinear perceptron

We propose a mutual learning method using nonlinear perceptron within the framework of online learning and have analyzed its validity using computer simulations. Mutual learning involving three or more students is fundamentally different from the two-student case with regard to variety when selecting a student to act as the teacher. The proposed method consists of two learning steps: first, multiple students learn independently from a teacher, and second, the students learn from others through mutual learning. Results showed that the mean squared error could be improved even if the teacher had not taken part in the mutual learning.