eprintid: 2890
rev_number: 6
eprint_status: archive
userid: 307
dir: disk0/00/00/28/90
datestamp: 2017-12-29 08:50:14
lastmod: 2017-12-29 08:50:14
status_changed: 2017-12-29 08:50:14
type: conference_item
metadata_visibility: show
creators_name: Nguyen, Thi Hong Khanh
creators_name: Tran, Trong Hieu
creators_name: Nguyen, Tran Van
creators_name: Le, Thi Thanh Luu
title: Merging Possibilistic Belief Bases by Argumentation
ispublished: pub
subjects: ElectronicsandComputerEngineering
divisions: fac_fit
abstract: 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.
date: 2017
official_url: https://doi.org/10.1007/978-3-319-54472-4_3
full_text_status: public
pres_type: paper
pagerange: 24-34
event_title: Intelligent Information and Database Systems - 9th Asian Conference, ACIIDS 2017, Kanazawa, Japan, April 3-5, 2017, Proceedings, Part I
event_type: conference
refereed: TRUE
citation:   Nguyen, Thi Hong Khanh and Tran, Trong Hieu and Nguyen, Tran Van and Le, Thi Thanh Luu  (2017) Merging Possibilistic Belief Bases by Argumentation.  In: Intelligent Information and Database Systems - 9th Asian Conference, ACIIDS 2017, Kanazawa, Japan, April 3-5, 2017, Proceedings, Part I.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2890/1/ACIIDS_2017.pdf