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INICIO | 23 de mayo de 2024
  

Knowledge revision in Markov networks.

Título inglés Knowledge revision in Markov networks.
Título español Revisión del conocimiento en redes de Markov.
Autor/es Gebhardt, Jörg ; Borgelt, Christian ; Kruse, Rudolf ; Detmer, Heinz
Organización Intellig. Syst. Consult. (ISC), Celle, Alemania;Dep. Knowl. Proc. Lang. Eng. Otto-von-Guericke-Univ. Magdeburg, Magdeburg, Alemania;Volkswagen Group, Wolfsburg, Alemania
Revista 1134-5632
Publicación 2004, 11 (2-3): 93-107, 20 Ref.
Tipo de documento articulo
Idioma Inglés
Resumen inglés A lot of research in graphical models has been devoted to developing correct and efficient evidence propagation methods, like join tree propagation or bucket elimination. With these methods it is possible to condition the represented probability distribution on given evidence, a reasoning process that is sometimes also called focusing. In practice, however, there is the additional need to revise the represented probability distribution in order to reflect some knowledge changes by satisfying new frame conditions. Pure evidence propagation methods, as implemented in the known commercial tools for graphical models, are unsuited for this task. In this paper we develop a consistent scheme for the important task of revising a Markov network so that it satisfies given (conditional) marginal distributions for some of the variables. This task is of high practical relevance as we demonstrate with a complex application for item planning and capacity management in the automotive industry at Volkswagen Group.
Clasificación UNESCO 120304
Palabras clave español Inteligencia artificial ; Planificación ; Proceso de Markov ; Grafos ; Distribución de probabilidad
Código MathReviews MR2139291
Código Z-Math Zbl 1129.68510
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Equipo DML-E
Instituto de Ciencias Matemáticas (ICMAT - CSIC)
rmm()icmat.es