Year: 1994
Type: article
Abstract: IBM AInuzdetz Resecrrcb Center, SCZnJo.w,Cul[fomia Abstroct.We provide a model for rcusonmg about knowledge and prob~bility together, We allow explicit mention of probabilities in formulas, so that our kmguagc has formu]as that essentially say "according to agent ~, formula p holds with probabi]lty at least b " The langutigc IS powerful enough to allow rewoning about higher-order proixibdities, as well w ti]lowing e~pliclt comparisons of the probabilities an agent places on distinct events.We present a general framcw(>rk for interpreting such formulas, and consider wmous properties that might hold of the interrclatmnship between agents' probability assignments at different states.We pro~,icte a complete axlomatization for reasoning about knowledge and probabihty, prove a small model property, and obtain decision procedures, We then consider the effects of adding common knowledge and a probabilistic variant of common knowledge to the language.
Source: Journal of the ACM
Authors: Ronald Fagin, Joseph Y. Halpern
Institution: IBM Research - Almaden
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W1480135136