An argumentation model based on evidence theory

机译：基于证据理论的论证模型

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摘要

Argumentation is a method for resolving differences between agents. Due to the uncertainty and the asymmetry of information, it is necessary to introduce uncertainty processing method into argument evaluation. In this paper, an argumentation model based on DS evidence theory is proposed, in which, an argument is extended to a rule with a premise and a conclusion, premises and conclusions are all called statements; and the uncertainty of a statement is evaluated by mass function of DS evidence theory, the uncertain value of statement is called opinion. Then, the argument evaluation algorithms are proposed to updating all statements' opinions in Argumentation model. Finally, an example is given to illustrate the validity of the method.

机译：论证是一种解决代理之间差异的方法。由于信息的不确定性和不对称性，有必要将不确定性处理方法引入参数评估。在本文中，提出了一种基于DS证据理论的论证模型，其中，争论延伸到一个规则，附近，结论，房地和结论都被称为陈述;声明的不确定性是通过DS证据理论的质量功能来评估的，声明的不确定价值称为意见。然后，建议参数评估算法在论证模型中更新所有陈述的意见。最后，给出了示例来说明方法的有效性。

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来源
《International Conference on computer science education》|2015年||共4页
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作者
Caiquan Xiong; Yifan Zhan; Shaobin Chen;
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中图分类计算技术、计算机技术;
关键词
Argumentation framework; evidence theory; uncertain inference;

机译：论证框架;证据理论;不确定的推理;

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An argumentation model based on evidence theory

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