pith. sign in

arxiv: 1304.1130 · v1 · pith:PRHEBOFInew · submitted 2013-03-27 · 💻 cs.AI

A Probabilistic Reasoning Environment

classification 💻 cs.AI
keywords knowledgeprobabilisticargumentsenvironmentlevelnetworkreasoningsystem
0
0 comments X
read the original abstract

A framework is presented for a computational theory of probabilistic argument. The Probabilistic Reasoning Environment encodes knowledge at three levels. At the deepest level are a set of schemata encoding the system's domain knowledge. This knowledge is used to build a set of second-level arguments, which are structured for efficient recapture of the knowledge used to construct them. Finally, at the top level is a Bayesian network constructed from the arguments. The system is designed to facilitate not just propagation of beliefs and assimilation of evidence, but also the dynamic process of constructing a belief network, evaluating its adequacy, and revising it when necessary.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.