International Journal of Internet, Broadcasting and Communication

  • 제14권2호
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  • Pages.192-198
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  • 2022
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  • 2288-4920(pISSN)
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  • 2288-4939(eISSN)
한국인터넷방송통신학회 (The Institute of Internet, Broadcasting and Communication)
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Reinforcement learning multi-agent using unsupervised learning in a distributed cloud environment

  • Gu, Seo-Yeon (Department of Computer Science, Kwangwoon University) ;
  • Moon, Seok-Jae (Department of Artificial Intelligence Institute of Information Technology, KwangWoon University) ;
  • Park, Byung-Joon (Department of Computer Science, Kwangwoon University)
  • 투고 : 2022.04.18
  • 심사 : 2022.04.22
  • 발행 : 2022.05.31
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초록

Companies are building and utilizing their own data analysis systems according to business characteristics in the distributed cloud. However, as businesses and data types become more complex and diverse, the demand for more efficient analytics has increased. In response to these demands, in this paper, we propose an unsupervised learning-based data analysis agent to which reinforcement learning is applied for effective data analysis. The proposal agent consists of reinforcement learning processing manager and unsupervised learning manager modules. These two modules configure an agent with k-means clustering on multiple nodes and then perform distributed training on multiple data sets. This enables data analysis in a relatively short time compared to conventional systems that perform analysis of large-scale data in one batch.

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과제정보

This work is financially supported by Korea Ministry of Environment(MOE) Graduate School specialized in Integrated Pollution Prevention and Control Project.

참고문헌

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