“…the vector of non-zero values |{ i : h i = j }| arranged in non-increasing order 11 . [For more details see for example [16].] This observation seems to us to point to the significance of this property and justifies us giving a name to it Clearly the principles Px and SN (for this binary language) follow from Sx.…”
Section: The Spectrum Exchangeability Principle (Sx)mentioning
We consider the problem of induction over languages containing binary relations and outline a way of interpreting and constructing a class of probability functions on the sentences of such a language. Some principles of inductive reasoning satisfied by these probability functions are discussed, leading in turn to a representation theorem for a more general class of probability functions satisfying these principles.
“…the vector of non-zero values |{ i : h i = j }| arranged in non-increasing order 11 . [For more details see for example [16].] This observation seems to us to point to the significance of this property and justifies us giving a name to it Clearly the principles Px and SN (for this binary language) follow from Sx.…”
Section: The Spectrum Exchangeability Principle (Sx)mentioning
We consider the problem of induction over languages containing binary relations and outline a way of interpreting and constructing a class of probability functions on the sentences of such a language. Some principles of inductive reasoning satisfied by these probability functions are discussed, leading in turn to a representation theorem for a more general class of probability functions satisfying these principles.
“…To emphasize the incompatibility of these two principles note, as shown in [14], that, away from the extreme cases, JSP implies Reichenbach's Axiom, and that Reichenbach's Axiom contradicts GPIR.…”
Section: Resultsmentioning
confidence: 99%
“…Finally, by the asymptotic consistency of Bayes posteriors (see for example Theorem 7.78 of [16] or page 25 of [14]) we see that the RHS of (15) converges to…”
Section: Gpir and The W δmentioning
confidence: 86%
“…For more on this, in particular the conditions under which equality can hold here, see [6], [9], [14]. The Generalized Principle of Instantial Relevance, GPIR, proposed in [8], [14] takes the intuition behind PIR a step further.…”
Section: The Generalized Principle Of Instantial Relevancementioning
confidence: 99%
“…The Generalized Principle of Instantial Relevance, GPIR, proposed in [8], [14] takes the intuition behind PIR a step further. In words, GPIR says that the observation of an object satisfying a set of properties should not decrease the belief in further objects satisfying a superset of those properties.…”
Section: The Generalized Principle Of Instantial Relevancementioning
In this paper we consider a natural generalization of the Principle of Instantial Relevance and give a complete characterization of the probabilistic belief functions satisfying this principle as a family of discrete probability functions parameterized by a single real δ ∈ [0, 1).
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