Implementing ∆ps (PS-Merge) Belief Merging Operator for Belief Revision



Document title: Implementing ∆ps (PS-Merge) Belief Merging Operator for Belief Revision
Journal: Computación y sistemas
Database: PERIÓDICA
System number: 000423348
ISSN: 1405-5546
Authors: 1
1
2
Institutions: 1Universidad Juárez Autónoma de Tabasco, División Académica de Informática y Sistemas, Cunduacán, Tabasco. México
2Bournemouth University, School of Design, Engineering and Computing, Bournemouth. Reino Unido
Year:
Season: Jul-Sep
Volumen: 21
Number: 3
Country: México
Language: Inglés
Document type: Artículo
Approach: Aplicado, descriptivo
English abstract Belief merging aims at combining information from multiple sources while belief revision studies strategies for retracting information in order to maintain consistency when the addition of new evidence to a belief base makes it inconsistent. An ordering of the sentences in the belief base is used to determine priorities among sentences so that those with lower priority can be identified and retracted. This ordering can be difficult to generate and maintain. To address this difficulty, in this paper we show how to generate automatically an ordering of the belief base sentences through the implementation of a belief merging operator. We extend the ∆ps (PS-Merge) belief merging operator in order to consider constraints, then we use this extension, called ∆ p s μ (∆ps under constraints), as a strategy for belief revision. We treat new evidence as a constraint and apply the extended merging operator to obtain the revised belief base. We propose several properties of this operator when compared to other two belief revision operators solving four examples described as real-life scenarios. Finally we show a software prototype based on this approach, called Belief Reviser, freely accessible online
Disciplines: Ciencias de la computación
Keyword: Procesamiento de datos,
Revisión de creencias,
Modelación del conocimiento,
Sistemas de soporte para decisiones
Keyword: Data processing,
Belief revision,
Knowledge modeling,
Decision support systems
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