Journal of Computational Intelligence in Materials Science
Received On : 02 November 2022
Revised On : 18 December 2022
Accepted On : 22 December 2022
Published On : 05 January 2023
Volume 01, Issue 01
Pages : 001-011
An Intelligent Agent (IA) is a type of autonomous entity in the field of Artificial Intelligence (AI) that gathers
information about its surroundings using sensors, takes action in response to that information using actuators ("agent"
part), and guides its behavior to achieve predetermined results (i.e. it is rational). Agents that are both intelligent and able
to learn or utilize information to accomplish their tasks would be ideal. Similar to how economists study agents,
cognitive scientists, ethicists, philosophers of practical reason and researchers in a wide range of other disciplines study
variations of the IAmodel used in multidisciplinary socio-cognitive modelling and computer social simulation models. In
this article, the term "Multi-Agent System" (MAS) has been used to refer to a system in which two or more autonomous
entities communicate with one another. The key objective of this research is to provide a critical analysis of MAS and its
applications in power systems. A case study to define the application of MAS in power system is also provided, using a
critical implementation of fuzzy logic controllers.
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The authors would like to thank to the reviewers for nice comments on the manuscript.
No funding was received to assist with the preparation of this manuscript.
Conflict of interest
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Availability of data and materials
No data available for above study.
All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.
Madeleine Wang Yue Dong
Madeleine Wang Yue Dong
School of Design, University of Washington, Seattle, WA.
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Cite this article
Madeleine Wang Yue Dong, “A Survey on Multi Agent System and Its Applications in Power System Engineering”, Journal of Computational Intelligence in Materials Science, vol.1, no.1, pp. 001-011, January 2023.