Belief Revision in Structured Probabilistic Argumentation

• Autores: Shakarian, Paulo; Simari, Gerardo; Falappa, Marcelo Alejandro
• Año de publicación: 2014
• Idioma: inglés
• Tipo de recurso: artículo
• Materia: Belief Revision; Probabilistic Argumentation; Cybersecurity
• Institución: Consejo Nacional de Investigaciones Científicas y Técnicas

In real-world applications, knowledge bases consisting of all the information at hand for a specific domain, along with the current state of affairs, are bound to contain contradictory data coming from different sources, as well as data with varying degrees of uncertainty attached. Likewise, an important aspect of the effort associated with maintaining knowledge bases is deciding what information is no longer useful; pieces of information (such as intelligence reports) may be outdated, may come from sources that have recently been discovered to be of low quality, or abundant evidence may be available that contradicts them. In this paper, we propose a probabilistic structured argumentation framework that arises from the extension of Presumptive Defeasible Logic Programming (PreDeLP) with probabilistic models, and argue that this formalism is capable of addressing the basic issues of handling contradictory and uncertain data. Then, to address the last issue, we focus on the study of non-prioritized belief revision operations over probabilistic PreDeLP programs. We propose a set of rationality postulates – based on well-known ones developed for classical knowledge bases – that characterize how such operations should behave, and study a class of operators along with theoretical relationships with the proposed postulates, including a representation theorem stating the equivalence between this class and the class of operators characterized by the postulates.
Fil: Shakarian, Paulo . U.S. Military Academy. Department of Electrical Engineering and Computer Science; Estados Unidos
Fil: Simari, Gerardo . University of Oxford; Reino Unido
Fil: Falappa, Marcelo Alejandro. Universidad Nacional del Sur. Departamento de Ciencia e Ingeniería de la Computación. Laboratorio de Investigación y Desarrollo en Inteligencia Artificial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina