Incompletely specified probabilistic networks

Probabilistic networks, used as an adjunct or alternative to the logical models used in AI and DSS, offer a way to compactly represent a distribution over a set of random variables. Nonetheless, the specification of a given network may require conditional probabilities which are simply unavailable. A means for analyzing incompletely specified networks is presented, and some general rules are derived from the application of the method to some simple networks.<<ETX>>

[1]  M. R. Novick,et al.  The Role of Exchangeability in Inference , 1981 .

[2]  Peter C. Cheeseman,et al.  A Method of Computing Generalized Bayesian Probability Values for Expert Systems , 1983, IJCAI.

[3]  David Heckerman,et al.  Probabilistic similarity networks , 1991, Networks.

[4]  Henk Sol,et al.  Proceedings of the 54th Hawaii International Conference on System Sciences , 1997, HICSS 2015.

[5]  Richard Scheines,et al.  Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modeling , 1987 .

[6]  Michael R. Genesereth,et al.  Logical foundations of artificial intelligence , 1987 .

[7]  Rodney W. Johnson,et al.  Axiomatic derivation of the principle of maximum entropy and the principle of minimum cross-entropy , 1980, IEEE Trans. Inf. Theory.

[8]  Michael P. Wellman.  Fundamental Concepts of Qualitative Probabilistic Networks , 1990, Artif. Intell..

[9]  Clifford H. Wagner.  Simpson's Paradox in Real Life , 1982 .

[10]  E. H. Simpson,et al.  The Interpretation of Interaction in Contingency Tables , 1951 .

[11]  Gregory F. Cooper,et al.  A Bayesian method for the induction of probabilistic networks from data , 1992, Machine-mediated learning.

[12]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[13]  David J. Spiegelhalter,et al.  A statistical view of uncertainty in expert systems , 1986 .

[14]  David J. Spiegelhalter,et al.  Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[15]  Raj Bhatnagar,et al.  Handling Uncertain Information: A Review of Numeric and Non-numeric Methods , 1985, UAI.

[16]  Richard E. Neapolitan,et al.  Probabilistic reasoning in expert systems - theory and algorithms , 2012 .

[17]  Ross D. Shachter.  Probabilistic Inference and Influence Diagrams , 1988, Oper. Res..

[18]  Gregory F. Cooper,et al.  A Bayesian Method for the Induction of Probabilistic Networks from Data , 1992 .