Deriving Optimal Solutions from Incomplete Knowledge Bases

摘要

Many real world domains can not be represented using Bayesian Networks due to theneed for complete probability tables and acyclic knowledge. However, Bayesian Knowledge Bases (BKBs) are a viable method for representing these incomplete domains, but very little research has been performed on inferencing with them. This paper presents three inference engines for extracting optimal solutions from