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Książka Generalized Jeffrey Conditionalization Dirk Draheim

Generalized Jeffrey Conditionalization

A Frequentist Semantics of Partial Conditionalization

Autor: Dirk Draheim
Język: Angielski
Oprawa: Miękka
Wydawca: Springer International Publishing AG
Dostępność: Dostępna u dostawcy w małych ilościach
Wysyłamy za 13-18 dni
240.46 zł
This book provides a frequentist semantics for conditionalization on partially known events, which i...

Informacje o książce

Autor
Dirk Draheim
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2017
strony
106
EAN
9783319698670
ISBN
3319698672
Enbook ID
18185022
Wydawca
Springer International Publishing AG
Waga
1883
Wymiary
155 x 235 x 7

Pełny opis

This book provides a frequentist semantics for conditionalization on partially known events, which is given as a straightforward generalization of classical conditional probability via so-called probability testbeds. It analyzes the resulting partial conditionalization, called frequentist partial (F.P.) conditionalization, from different angles, i.e., with respect to partitions, segmentation, independence, and chaining. It turns out that F.P. conditionalization meets and generalizes Jeffrey conditionalization, i.e., from partitions to arbitrary collections of events, opening it for reassessment and a range of potential applications. A counterpart of Jeffrey's rule for the case of independence holds in our frequentist semantics. This result is compared to Jeffrey's commutative chaining of independent updates. The postulate of Jeffrey's probability kinematics, which is rooted in the subjectivism of Frank P. Ramsey, is found to be a consequence in our frequentist semantics. This way the book creates a link between the Kolmogorov system of probability and one of the important Bayesian frameworks. Furthermore, it shows a preservation result for conditional probabilities under the full update range and compares F.P. semantics with an operational semantics of classical conditional probability in terms of so-called conditional events. Lastly, it looks at the subjectivist notion of desirabilities and proposes a more fine-grained analysis of desirabilities a posteriori. This book appeals to researchers who are involved in any kind of knowledge processing systems. F.P. conditionalization is a straightforward, fundamental concept that fits human intuition, and is systematically linked to one of the important Bayesian frameworks. As such, the book is interesting for anybody investigating the semantics of reasoning systems.

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