KNET: Integrating hypermedia and normative Bayesian modeling

Chavez RM, Cooper GF. KNET: Integrating hypermedia and normative Bayesian modeling. In: Uncertainty in Artificial Intelligence 4 (North-Holland, Amsterdam, 1990) 339–349.

KNET is a general-purpose shell for constructing expert systems based on belief networks and decision networks. Such networks serve as graphical representations for decision models, in which the knowledge engineer must define clearly the alternatives, states, preferences, and relationships that constitute a decision basis. KNET contains a knowledge-engineering core written in Object Pascal and an interface that integrates HyperCard, a hypertext authoring tool for the Apple Macintosh computer, into an e.;cpert-system architecture. Hypertext and hypermedia have become increasingly sophisticated in their storage, management, and retrieval of information. In broad terms, hypermedia deliver heterogeneous bits of information in dynamic, extensively crossreferenced packages. The resulting KNET system features a coherent probabilistic scheme for managing uncertainty, an object-oriented graphics editor for drawing and manipulating decision networks, and HyperCard's potential for quickly constructing flexible and friendly user interfaces. We envision KNET as a useful prototyping tool for ongoing research on a variety of Bayesian reasoning problems, including tractable representation, inference, and explanation.

Publication Year: 
1990
Faculty Author: 
Publication Credits: 
Chavez RM, Cooper GF.
AttachmentSize
PDF icon Chaves Cooper KNET.pdf739.81 KB
^