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Handbook of Defeasible Reasoning and Uncertainty Management Systems pp 477–510Cite as

Network-Based Decision Algorithms

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Part of the book series: Handbook of Defeasible Reasoning and Uncertainty Management Systems ((HAND,volume 5))

Abstract

Decision making under uncertainty is a common problem in the real world. Decision analysis provides a method that helps the decision maker to select an appropriate decision alternative in the face of uncertain environment. Traditional decision analysis is based on Bayesian probability theory and utility theory. The uncertain states of nature are represented by probabilities, and the optimal decision is the one that optimizes its expected utility, where the expectation is taken by using the probability function that represents the uncertainty about which state of affair will prevail. Decision Tree [Raiffa, 19681 was one of the first frameworks for representing and solving decision problems. However, this approach is not widely accepted into practice due to their weakness of modeling uncertainty, modeling information constraints, and the combinatorial explosiveness for a complicated problem.

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Author information

Authors and Affiliations

  1. IRIDIA-Université Libre de Bruxelles, Belgium

    Hong Xu

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  1. Hong Xu
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Editors and Affiliations

  1. University of Fribourg, Switzerland

    Jürg Kohlas

  2. Universidad de Granada, Spain

    Serafín Moral

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© 2000 Springer Science+Business Media Dordrecht

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Xu, H. (2000). Network-Based Decision Algorithms. In: Kohlas, J., Moral, S. (eds) Handbook of Defeasible Reasoning and Uncertainty Management Systems. Handbook of Defeasible Reasoning and Uncertainty Management Systems, vol 5. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-1737-3_11

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  • DOI: https://doi.org/10.1007/978-94-017-1737-3_11

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-5603-0

  • Online ISBN: 978-94-017-1737-3

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