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Real-World Applications of Influence Diagrams

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Advances in Bayesian Networks

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 146))

Abstract

It is very well known the difficulties involved in making decisions between different alternatives. A substantial amount of empirical evidence demonstrates that this is something inherent in human beings. That is the reason why there is a major focus on methods and techniques for aiding to overcome the deficiencies of human judgment and decision making. Decision theory is the mathematical foundation for rational decision making, combining probability theory and utility theory. Decision analysis studies the application of decision theory to decision problems. This research have provided several results, one of them being Influence Diagrams (IDs) . An ID is a graphical model with two important features: a) gives a powerful tool to capture all the decision problem elements and b) can be evaluated providing optimal policies for decision makers. These reasons explain the extensive body of work devoted to IDs and the use of this tool in real-world applications.

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Authors and Affiliations

  1. Dpt. of Computer Science and Artificial Intelligence, University of Granada, c/ Periodista Daniel Saucedo Aranda, s/n, Granada, 18071, Spain

    Manuel Gómez

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  1. Manuel Gómez
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  1. Escuela Politecnica Superior, Depto. Informatica, Universidad de Castilla-La Mancha, Campus Universitario s/n, 02071, Albacete, Spain

    José A. Gámez

  2. ETS Ingenieria Informatica, Depto. Ciencias Computacion, Universidad de Granada, Campus Universitario Fuentenueva, 18071, Granada, Spain

    Serafín Moral

  3. ETS Ingenieria Informatica, Depto. Estadistica y Matemática Aplicada, Universidad de Almeria, La Cañada de San Urbano s/n, 04120, Almeria, Spain

    Antonio Salmerón

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© 2004 Springer-Verlag Berlin Heidelberg

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Gómez, M. (2004). Real-World Applications of Influence Diagrams. In: Gámez, J.A., Moral, S., Salmerón, A. (eds) Advances in Bayesian Networks. Studies in Fuzziness and Soft Computing, vol 146. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39879-0_9

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  • DOI: https://doi.org/10.1007/978-3-540-39879-0_9

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  • Print ISBN: 978-3-642-05885-1

  • Online ISBN: 978-3-540-39879-0

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