In this paper we refer to an axiomatic definition of T-conditional possibility, where T is any t-norm. We characterize a full T-conditional possibility in terms of a suitable set of unconditional possibilities. Starting from this characterization we are able to manage coherent conditional possibility assessments and their enlargements. To compare T-conditional possibility related to different t-norm T, we study binary relations locally representable by a T-conditional possibility. © 2008 Elsevier B.V. All rights reserved
AbstractAny dynamic decision model needs to deal with conditional events and conditional uncertainty...
We investigate the idea of representing conditional measures as simple measures (possibly with furth...
AbstractIn this paper, a semantic basis for Possibility Theory based on likelihood functions is pres...
Any dynamic decision model or procedure for acquisition of knowledge must deal with conditional even...
In probability theory the notion of coherence has been introduced by de Finetti in terms of bets and...
The subtle notion of conditioning is controversial in several contexts, for example in possibility t...
In this paper we consider coherent T-conditional possibility assessments, with T a continuous t-norm...
From a knowledge representation point of view, it may be interesting to distinguish between (i) what...
AbstractPossibility measures and conditional possibility measures are given a behavioural interpreta...
We deal with conditional probability in the sense of de Finetti and with T-conditional possibility (...
Any dynamic decision model needs to deal with conditional events and conditional uncertainty measure...
It is shown that the notion of conditional possibility can be consistently introduced in possibility...
AbstractThe concept of conditioning is well known in probability theory, where it is used in artific...
AbstractThe notion of conditional possibility derived from marginal possibility measures has receive...
Adams’s Thesis, the claim that the probabilities of indicative conditionals equal the conditional pr...
AbstractAny dynamic decision model needs to deal with conditional events and conditional uncertainty...
We investigate the idea of representing conditional measures as simple measures (possibly with furth...
AbstractIn this paper, a semantic basis for Possibility Theory based on likelihood functions is pres...
Any dynamic decision model or procedure for acquisition of knowledge must deal with conditional even...
In probability theory the notion of coherence has been introduced by de Finetti in terms of bets and...
The subtle notion of conditioning is controversial in several contexts, for example in possibility t...
In this paper we consider coherent T-conditional possibility assessments, with T a continuous t-norm...
From a knowledge representation point of view, it may be interesting to distinguish between (i) what...
AbstractPossibility measures and conditional possibility measures are given a behavioural interpreta...
We deal with conditional probability in the sense of de Finetti and with T-conditional possibility (...
Any dynamic decision model needs to deal with conditional events and conditional uncertainty measure...
It is shown that the notion of conditional possibility can be consistently introduced in possibility...
AbstractThe concept of conditioning is well known in probability theory, where it is used in artific...
AbstractThe notion of conditional possibility derived from marginal possibility measures has receive...
Adams’s Thesis, the claim that the probabilities of indicative conditionals equal the conditional pr...
AbstractAny dynamic decision model needs to deal with conditional events and conditional uncertainty...
We investigate the idea of representing conditional measures as simple measures (possibly with furth...
AbstractIn this paper, a semantic basis for Possibility Theory based on likelihood functions is pres...