`Plausibilities of plausibilities': an approach through circumstances

dc.creatorMana, P. G. L. Porta
dc.creatorMånsson, A.
dc.creatorBjörk, G.
dc.date2006-07-17
dc.date2007-04-29
dc.date.accessioned2026-07-07T07:58:30Z
dc.date.available2026-07-07T07:58:30Z
dc.descriptionProbability-like parameters appearing in some statistical models, and their prior distributions, are reinterpreted through the notion of `circumstance', a term which stands for any piece of knowledge that is useful in assigning a probability and that satisfies some additional logical properties. The idea, which can be traced to Laplace and Jaynes, is that the usual inferential reasonings about the probability-like parameters of a statistical model can be conceived as reasonings about equivalence classes of `circumstances' - viz., real or hypothetical pieces of knowledge, like e.g. physical hypotheses, that are useful in assigning a probability and satisfy some additional logical properties - that are uniquely indexed by the probability distributions they lead to.
dc.description30 pages, 3 figures. V2: clarified some points and corrected some typos. V3: corrected typos and added references
dc.identifierhttps://arxiv.org/abs/quant-ph/0607111
dc.identifierhttp://arxiv.org/abs/quant-ph/0607111
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/128031
dc.subjectQuantum Physics
dc.subjectArtificial Intelligence
dc.title`Plausibilities of plausibilities': an approach through circumstances
dc.typetext

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