Publications and On-Line Technical reports related to GRAPHICAL-BELIEF
This file contains a list of publications and technical reports
releated to the Graphical-Belief project. As many
of them were never published except in a rather limited technical
report series, I'm making PDFs available for download here.
Follow this link for a more complete list of
my publications.
This book is a good introduction to the theory of graphical belief
function models and provides a good solid grounding in the theoretical
basis of both BELIEF and
Graphical-Belief.
- Almond, R.G. [1995a]
- Graphical Belief Modeling Chapman and Hall (Click Here For
Ordering Information. (ISBN 0-412-06661-0). Revised
version of Fusion and Propagation in Graphical Belief
Models: An Implementation and an Example. Ph.D.
dissertation and Harvard University, Department of
Statistics Technical Report S-130.
Overviews and Examples
These two papers were written as examples of
Graphical-Belief in action. Although they are now
somewhat dated, they provide a good overview of the kinds of problems
Graphical-Belief can address and review some of the
basic properties of the system.
- Almond, R.G. [1992]
- ``An Extended Example for Testing GRAPHICAL-BELIEF.'' StatSci
Research Report 6. (PDF) This example
goes over the simple reliability example from Martz and Waller [1990].
- Almond, R.G. and Madigan, D. [1993]
- ``Using GRAPHICAL-BELIEF to Predict Risk or Coronary Artery
Disease.'' StatSci Research Report 19. (PDF) This example
goes over a simple medical risk example fit to data from
Detrano et al. [1989].
Published Papers
This section lists various papers available in published journals and
conference proceedings related to the
Graphical-Belief project.
- Madigan, D., K. Mosurski and R.G. Almond [1997]
- ``Graphical Explanation in Belief Networks.'' Journal of
Computational and Graphical Statistics, 6, 160-181.
- Madigan, D. and R.G. Almond [1995]
- ``Test Selection Strategies for Belief Networks'' StatSci
Research Report 20. In D. Fisher and H.J. Lenz (eds)
Learning from Data: AI and Statistics V Springer-Verlag, pp 89-98.
Describes the use of weight of evidence to select tests.
- Almond, R. G., Bradshaw, J.M., Madigan, D. [1994]
- ``Reuse and Sharing of Graphical Belief Network
Components.'' in P. Cheeseman and W. Oldford (eds.)
Selecting Models from Data: Artificial Intelligence and
Statistics IV, Springer-Verlag, 113--122. Describes the
basic knowledge structures used in graphical belief models.
- Madigan, D., Raftery, A. E., York, J. C., Bradshaw, J. M.
and Almond, R. G. [1994]
- ``Strategies for Graphical Model Selection.'' in P.
Cheeseman and W. Oldford (eds.) Selecting Models from
Data: Artificial Intelligence and Statistics IV,
Springer-Verlag, 91--100. Compares two techniques for
selecting models from data accounting for model uncertainty.
- Madigan, D., York, J.C. Bradshaw, J.M. and Almond, R.G. [1994]
- ``Bayesian Graphical Models for Predicting Errors in
Databases.'' in P. Cheeseman and W. Oldford (eds.)
Selecting Models from Data: Artificial Intelligence and
Statistics IV, Springer-Verlag, 123--132. Describes an
application of graphical models.
- Almond, R.G. [1993]
- ``Lack of Information Based Control in Expert Systems.''
In Hand, D.J (ed). Artificial Intelligence Frontiers in
Statistics: AI and Statistics III, Chapman and Hall,
pp 82--89. Describes a technique for tracing information
through a graphical model.
- Bradshaw, J.M., Chapman, C.R., Sullivan, K.M., Almond,
R.G., Madigan, D., Zarley, D., Gavrin, J., Nims, J., and
Bush, N. [1992].
- ``KS-3000: an application of DDUCKS to bone-marrow
transplant patient support.'' In Proceedings of the
Sixth Annual Florida AI Research Symposium (FLAIRS
'93), Ft. Lauderdale, FL, 78--83. Describes an application
in which a graphical model engine is embedded in a more complex
knowledge based performance support system.
(Word Document)
- Almond, Russell G. [1991]
- ``Building Blocks for Graphical Belief Models.''
Journal Of Applied Statistics, 18,
63--76. Describes some simple belief function models.
- Almond, R.G. [1988]
- ``Fusion and Propagation in Graphical Belief Models.''
Computing Science and Statistics: Proceedings of the
20th Symposium on the Interface. Wegman, Edward J.,
Gantz, Donald T. and Miller, John J. (ed.). American
Statistical Association, Alexandria, Virginia. pp
365--370. (Click Here to
Download an extended version.) Describes a simple example
of a graphical belief function.
Technical Reports and Prepublications
The following reports and conference presentations describe important
developments in the graphical belief project.
- Almond, R.G. [1995]
- ``Hypergraph Grammars for Knowledge Based Model
Construction.'' StatSci Research Report 23. Presented at
the 5th International Workshop on AI and
Statistics, Ft. Lauderdale Florida. (Click Here to Download) This report
describes the object-oriented model construction features.
- Almond, R.G. [1995]
- ``Capturing Reliability Knowledge in GRAPHICAL-BELIEF.''
StatSci Research Report 31. Presented in special NASA
collection. (Click Here to
Download) Describes how the object-oriented model
construction would work in a distributed engineering
environment.
- Almond, R.G. [1994]
- ``Brushing Histories to Compare Models'' StatSci Research
Report 17. (Under Revision for Publication). (Click Here to Download) Shows the
mechanism used to compare changes in the model and study sensitivity.
- Almond, R.G. [1992]
- ``Models for Incomplete Failure Data.'' StatSci Research
Report 9. (Click Here to
Download) Describes the difference between belief function and
probability models.
Old Technical Reports
These are older technical reports which have largely been superceded
by more recent material. They occasionally contain material of
historical interest or which is not available elsewhere.
- Almond, R.G. [1992]
- ``Reduced Parameter Representation of Model Components'',
StatSci Research Report 1. (Click Here to
Download) This describes a mechanism for finding structure
within the rules which define the relationships among a few
variables.
- Almond, R.G. [1991]
- ``Fiducial Inference and Belief Functions.'' Technical Report
206, University of Washington, Department of Statistics. (Click Here to Download) Describes the
origins of belief functions from Fisher's ideas about fiducial
inference.
- Almond, R.G. and Kong, C-T. A. [1991]
- ``Some Heuristics for Building an Optimal Tree of Cliques from
a Graph or Hypergraph.'' University of Chicago, Department of
Statistics, Research Report 329. (Click
Here to Download) This describes the procedure for
building the junction tree. Most of the key results are
available in the book.
Explore an example of Graphical-Belief in
action.
Get more
information about obtaining Graphical-Belief .
Go to the home page for Russell Almond , author of Graphical-Belief.
Russell Almond, <lastname> (at) acm.org
Last modified: Jan 9 2006