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- W4304974377 abstract "Multi-agent systems (MASs) are defined as a group of interacting entities or agents sharing a common environment that changes over time, with capabilities of perception and action, and the mechanisms for their coordination provide a modern perspective on systems that traditionally were regarded as centralized. The main characteristics of agents are learning and adaptation. In the last few years, MASs have received tremendous attention from scholars in different fields. However, there are still challenges faced by MASs and their integration with machine learning (ML) methods. The primary goal of the study is to provide a broad review of the current developments in the field of MASs combined with ML methods. First, we present features of MASs considering the ML perspective. Second, we provide a classification of applications of MASs combined with ML methods. Third, we present a density map of applications in E-learning, manufacturing, and commerce. We expect this study to serve as a comprehensive resource for researchers and practitioners in the area." @default.
- W4304974377 created "2022-10-14" @default.
- W4304974377 creator A5012194690 @default.
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- W4304974377 date "2023-01-25" @default.
- W4304974377 modified "2023-10-01" @default.
- W4304974377 title "A State-of-the-Art Survey on Various Domains of Multi-Agent Systems and Machine Learning" @default.
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- W4304974377 doi "https://doi.org/10.5772/intechopen.107109" @default.
- W4304974377 hasPublicationYear "2023" @default.
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