Generalized belief change with imprecise probabilities and graphical models [Tesi di dottorato]

We provide a theoretical investigation of probabilistic belief revision in complex frameworks, under extended conditions of uncertainty, inconsistency and imprecision. We motivate our kinematical approach by specializing our discussion to probabilistic reasoning with graphical models, whose modular representation allows for efficient inference. Most results in this direction are derived from the relevant work of Chan and Darwiche (2005), that first proved the inter-reducibility of virtual and probabilistic evidence. Such forms of information, deeply distinct in their meaning, are extended to the conditional and imprecise frameworks, allowing further generalizations, e.g. to experts' qualitative assessments. Belief aggregation and iterated revision of a rational agent's belief are also explored.

diritti: info:eu-repo/semantics/openAccess
In relazione con info:eu-repo/semantics/altIdentifier/hdl/11573/1156672
CONTI, Pier Luigi
tutor esterni: A. Antonucci, P. Vicard
valutatori esterni: C.P. De Campos, C. Tarantola
CONTI, Pier Luigi
Settore SECS-S/01 - - Statistica

Tesi di dottorato. | Lingua: Inglese. | Paese: | BID: TD18044623