Innovative Construction of Reinforcement Learning Model for Information Fusion in Music Education

Abstract

In order to improve the effect of modern music education, this paper applies the digital information technology of music resources to the construction of the music teaching system and derives two new types of semi-decision-making process reinforcement learning algorithms based on the Bellman optimality equation base on discrete time. Moreover, this paper uses the comparative research methods to obtain the Q-value learning curve of the incremental value iterative reinforcement learning algorithm based on the semi-Markov decision process and the incremental value iterative reinforcement learning algorithm based on the dichotomy to improve the fusion effect of music teaching resources. Finally, this paper combines the actual needs of modern music education to construct an intelligent music teaching model.