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A Complex Networked Method of Sorting Negotiation Demand Based on Answer Set Programs

Hui Wang, Liang Li, Long-yun Gao, Wu Chen

College of Computer and Information Science, Southwest University, Chongqing, China

* Corresponding Author: Wu Chen,

Intelligent Automation & Soft Computing 2018, 24(1), 35-40.


With the development of big data science, handling intensive knowledge in the complex network becomes more and more important. Knowledge representation of multi-agent negotiation in the complex network plays an important role in big data science. As a modern approach to declarative programming, answer set programming is widely applied in representing the multi-agent negotiation knowledge in recent years. But almost all the relevant negotiation models are based on complete rational agents, which make the negotiation process complex and low efficient. Sorting negotiation demands is the most key step in creating an efficient negotiation model to improve the negotiation ability of agents. Traditional sorting method is not suitable for the negotiation in the complex network. In this paper, we propose a complex networked negotiation, which can show the relationships among demands, and then a sorting method of negotiation demands is proposed based on demand relationships. What’s more, we use the betweenness of literals and the boundary co-efficient of rules to evaluate the importance of demands and rules.


Cite This Article

H. Wang, . L. Li, . L. Gao and . W. Chen, "A complex networked method of sorting negotiation demand based on answer set programs," Intelligent Automation & Soft Computing, vol. 24, no.1, pp. 35–40, 2018.

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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