Merging Possibilistic Belief Bases by Argumentation

被引：2
作者：
Thi Hong Khanh Nguyen [1 ]
Trong Hieu Tran [2 ]
Tran Van Nguyen [2 ]
Thi Thanh Luu Le [2 ]
机构：
[1] Elect Power Univ Vietnam, Hanoi, Vietnam
[2] Vietnam Natl Univ, Hanoi, Vietnam
来源：
INTELLIGENT INFORMATION AND DATABASE SYSTEMS, ACIIDS 2017, PT I | 2017年 / 10191卷
关键词：
Belief merging; Argumentation; KNOWLEDGE BASES; FUSION; MODEL;
D O I：
10.1007/978-3-319-54472-4_3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Belief merging is one of active research fields with a large range of applications in Artificial Intelligence. Most of the work in this research field is in the centralized approach, however, it is difficult to apply to interactive systems such as multi-agent systems. In this paper, we introduce a new argumentation framework for belief merging. To this end, a constructive model to merge possiblistic belief bases built based on the famous general argumentation framework is proposed. An axiomatic model, including a set of rational and intuitive postulates to characterize the merging result is introduced and several logical properties are mentioned and discussed.
引用
收藏
页码：24 / 34
页数：11
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