A computation method in robust Bayesian decision theory

Abstract : We propose a method for computing the range of the optimal decisions when the utility function runs through a class u. The class u has constraints on the values and the shape of the utility functions. A discretization method enables to easily approximate the optimal decision associated with a particular utility function u is an element of u . The range of optimal decisions is computed by a Monte Carlo optimization method. An example is provided with numerical results.
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International Journal of Approximate Reasoning, Elsevier, 2009, 50 (2), pp.289-302. 〈10.1016/j.ijar.2008.03.021〉
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https://hal.inria.fr/hal-00858528
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Soumis le : jeudi 5 septembre 2013 - 15:35:33
Dernière modification le : jeudi 20 juillet 2017 - 16:33:39

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Christophe Abraham. A computation method in robust Bayesian decision theory. International Journal of Approximate Reasoning, Elsevier, 2009, 50 (2), pp.289-302. 〈10.1016/j.ijar.2008.03.021〉. 〈hal-00858528〉

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