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Evaluation of factors affecting dance training effects based on reinforcement learning

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Abstract

The traditional dance training process lacks a certain degree of scientificity due to the lack of precise motion capture and analysis system, which directly affects the final training effect. In view of the robust limitations of the type 1 fuzzy reinforcement learning flexible structure control system to the uncertainty of noise interference, based on the reinforcement learning algorithm, this paper proposes a flexible structure controller based on the type 2 fuzzy reinforcement learning algorithm. Moreover, this paper uses fuzzy sets with equidistant fuzzy centers to divide large-scale state or continuous state space into two types of fuzzy divisions, divide the action space uniformly, and build fuzzy rules based on the basic ideas of type 1 fuzzy reinforcement learning. In addition, this paper constructs an evaluation system for factors affecting dance training effects based on reinforcement learning and designs experiments to verify the performance of the system. The research results show that the system constructed in this paper meets the theoretical needs and can be applied to dance training practice later.

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Authors and Affiliations

  1. Department of Music and Dance College, Huaihua University, Huaihua, China

    Liu Xin

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  1. Liu Xin
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Correspondence to Liu Xin.

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The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

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Xin, L. Evaluation of factors affecting dance training effects based on reinforcement learning. Neural Comput & Applic 34, 6773–6785 (2022). https://doi.org/10.1007/s00521-021-06032-4

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  • DOI: https://doi.org/10.1007/s00521-021-06032-4

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