KSL-93-42 +, KSL-93-14 + redirect page
Graph-Grammar Assistance for Automated Generation of Influence Diagrams + Has identifier
Graph-Grammar Assistance for Automated Generation of Influence Diagrams + Ksl tr id
Graph-Grammar Assistance for Automated Generation of Influence Diagrams + Number
| Graph-Grammar Assistance for Automated Generation of Influence Diagrams |
Bibtype
techreport
Has publishing details
1994
Has title
Graph-Grammar Assistance for Automated Generation of Influence Diagrams
Has where published
KSL-93-42
Has year
1994
Title
Graph-Grammar Assistance for Automated Generation of Influence Diagrams
Year
1994
Abstract
One of the most difficult aspects of model … One of the most difficult aspects of modeling complex dilemmas in decision-analytic terms is composing a diagram of relevance relations from a set of domain concepts. Decision models in domains such as medicine, however, exhibit certain prototypical patterns that can guide the modeling process. Medical concepts can be classified according to semantic types that have characteristic positions and typical roles in an influence-diagram model. We have developed a graph-grammar production system that uses such inherent interrelationships among medical terms to facilitate the modeling of medical decisions. Our findings suggest that similar syntactic patterns can also lead to automated construction of decision models in domains other than medicine. ion models in domains other than medicine.
Note
Updated November 1994 Update submitted to KSL March 1995.
Author
John W. Egar and Mark A. Musen +
Has author
John W. Egar and Mark A. Musen +
Has identifier
Graph-Grammar Assistance for Automated Generation of Influence Diagrams +
Institution
Knowledge Systems, AI Laboratory +
Ksl tr id
Graph-Grammar Assistance for Automated Generation of Influence Diagrams +
Number
Graph-Grammar Assistance for Automated Generation of Influence Diagrams +
Process note
YES +
Categories KSL Technical Report +, Publication +, Technical Report +
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