Decision Making in a Context where Uncertainty is Represented by Belief Functions. (2000)
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@MISC{Smets00decisionmaking,
author = {Philippe Smets},
title = {Decision Making in a Context where Uncertainty is Represented by Belief Functions.},
year = {2000}
}
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Abstract
A quantified model to represent uncertainty is incomplete if its use in a decision environment is not explained. When belief functions were first introduced to represent quantified uncertainty, no associated decision model was proposed. Since then, it became clear that the belief functions meaning is multiple. The models based on belief functions could be understood as an upper and lower probabilities model, as the hint model, as the transferable belief model and as a probability model extended to modal propositions. These models are mathematically identical at the static level, their behaviors diverge at their dynamic level (under conditioning and/or revision). For decision making, some authors defend that decisions must be based on expected utilities, in which case a probability function must be determined. When uncertainty is represented by belief functions, the choice of the appropriate probability function must be explained and justified. This probability function doe...
Keyphrases
belief function decision making probability model appropriate probability function quantified model hint model belief function meaning probability function doe dynamic level transferable belief model decision environment probability function quantified uncertainty associated decision model static level
