| G. de Cooman and D. Ayles. Supremum preserving upper probabilities. Information Sciences, 1998. |
....should not be interpreted as probabilities, instead there is a surjective (onto) mapping from the belief space to the probability space. Belief and possibility functions have been interpreted as upper and lower probability bounds respectively (see e.g. Halpern Fagin [16] and de Cooman Ayles [17]) Belief functions can be useful for estimating probability values but not to set bounds, because the probability of a real event can never be determined with absolute certainty, and neither can upper and lower bounds to it. Our view is that probability always is a subjective notion, inasmuch as ....
G. de Cooman and D. Ayles. Supremum preserving upper probabilities. Information Sciences, 1998.
....where we propose to use possibilistic probabilities to model the linguistic probability assessments. Possibilistic probabilities can be interpreted as a model where the second order uncertainty is represented by a possibility measure, which is a special type of coherent imprecise probability model [5]. A justi cation for using a possibility measure for modelling linguistic assessments can be found in [4, 14, 16] Two types of possibilistic second order models can be distinguished: global models, as in [15] where the second order uncertainty concerns an unknown probability measure; and local ....
G. de Cooman and D. Aeyels. Supremum preserving upper probabilities. Information Sciences, 118:173-212, 1998.
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G. de Cooman and D. Ayles. Supremum preserving upper probabilities. Information Sciences, 1998.
No context found.
G. de Cooman, D. Aeyels. Supremum preserving upper probabilities. Information Sciences, 118:173--212, 1999.
No context found.
G. de Cooman and D. Ayles. Supremum preserving upper probabilities. Information Sciences, 1998.
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