Por Nino Guallart (Universidade de Sevilha, visiting fellow CFCUL/GI1).

Modal probability logics are usually interpreted under some variation of Kripkean models in which a probability measure is added. This conveniently represents objective probabilities, but presents some disadvantages when representing subjective probabilities, mainly that they need to have a definite fixed value. We propose the use of nested neighbourhood models with a probability for subjective probabilities, which can be imprecise probabilities (i.e, probabilities with a lower or upper bound instead of a definite value). Thus, we defend the use of neighbourhood models for subjective probabilities, and we consider some extensions of this, such as the representation of the combination of different probabilities, showing the easiness of the implementation of them in neighbourhood models.

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