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Research on Agent-Based Economic Decision Model Systems

by Chenxi Liu, Suchun Yang

1 College of Economics and Management, Shandong University of Science and Technology, Qingdao, 266590, China
2 School of Civil Engineering, Qingdao University of Technology, Qingdao, 266033, China

* Corresponding Author: Suchun Yang. Email: email

Intelligent Automation & Soft Computing 2020, 26(5), 1035-1046. https://doi.org/10.32604/iasc.2020.010135

Abstract

Based on an analysis of the development of economic decision support systems, agents are applied to construct intelligent economic decision support systems. This paper proposes a task-oriented agent design concept and designs multiple types of agents to complete the decision-making tasks with the task as the core. The structure of multi-agent based systems is provided, and the concrete realization structure of different types of agents in the system is also provided. Additionally, this study discusses the operational mechanism of the whole system and the cooperation between multiple agents in the system. Finally, these functions are implemented through a combination of VC++ 6.0, multi-threading technology and the expert system tool CLIPS. The economic decision support system combines complex system theory, decision theory, information collection, knowledge discovery technology, economic decision making and simulation technology. It can aid users in making decisions by using communication and cooperation between multiple agents.

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APA Style
Liu, C., Yang, S. (2020). Research on agent-based economic decision model systems. Intelligent Automation & Soft Computing, 26(5), 1035-1046. https://doi.org/10.32604/iasc.2020.010135
Vancouver Style
Liu C, Yang S. Research on agent-based economic decision model systems. Intell Automat Soft Comput . 2020;26(5):1035-1046 https://doi.org/10.32604/iasc.2020.010135
IEEE Style
C. Liu and S. Yang, “Research on Agent-Based Economic Decision Model Systems,” Intell. Automat. Soft Comput. , vol. 26, no. 5, pp. 1035-1046, 2020. https://doi.org/10.32604/iasc.2020.010135



cc Copyright © 2020 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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