Uncertainty and Persistence: a Bayesian Update Semantics for Probabilistic Expressions
| Autor: | Deniz Rudin |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
060201 languages & linguistics
Theoretical computer science Bayesian probability Probabilistic logic 06 humanities and the arts Belief revision 0603 philosophy ethics and religion Semantics computer.software_genre Philosophy 060302 philosophy 0602 languages and literature Data mining Persistence (discontinuity) Set (psychology) Implementation computer Natural language Mathematics |
| Zdroj: | Journal of Philosophical Logic. 47:365-405 |
| ISSN: | 1573-0433 0022-3611 |
| Popis: | This paper presents a general-purpose update semantics for expressions of subjective uncertainty in natural language. First, a set of desiderata are established for how expressions of subjective uncertainty should behave in dynamic, update-based semantic systems; then extant implementations of expressions of subjective uncertainty in such models are evaluated and found wanting; finally, a new update semantics is proposed. The desiderata at the heart of this paper center around the contention that expressions of subjective uncertainty express beliefs which are not persistent (i.e. beliefs that won’t necessarily survive the addition of new information that is compatible with all previous information), whereas propositions express beliefs that are persistent. I argue that if we make the move of treating updates in a dynamic semantics as Bayesian updates, i.e. as conditionalization, then expressions of subjective uncertainty will behave the way we want them to without altering the way propositions behave. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink