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Erschienen in:
27.05.2020 | Original Article
RETRACTED ARTICLE: Optimization analysis of sport pattern driven by machine learning and multi-agent
Erschienen in: Neural Computing and Applications | Ausgabe 4/2021
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Abstract
The intelligent simulation of Sports can match the actual game and is of great significance to the development of Sports. Sports is a system in which multiple agents work together. Compared with a single agent, the learning space of multiple agents increases sharply as the number of agents increases, so the learning difficulty increases. Therefore, based on machine learning technology, this study combines with the actual situation to build a Sports simulation system. Moreover, after establishing a more reasonable team defensive formation and strategy, the overall movement of the agent is optimized, and the corresponding structural model has been established in combination with various actions. In addition, this study designs a controlled trial to analyze the performance of the model. The research shows that the proposed method has certain effects and can provide theoretical reference for subsequent related research.