**References**

**Applications**

[GHVW98]
Grois, E., Hsu, W. H., Voloshin, M., & Wilkins, D. C. (1998). Bayesian Network
Models for Automatic Generation of Crisis Management Training Scenarios. In
*Proceedings of the Tenth Innovative Applications of Artificial Intelligence
Conference (IAAI-98)*, Madison, WI, pp. 1113-1120. Menlo Park, CA: AAAI
Press. **(PDF
/ PostScript
/
.ps.gz)**

**General**

[Br95]
Brooks, F. P. (1995). *The
Mythical-Man Month, 20th Anniversary Edition: Essays on Software Engineering*.
Boston, MA: Addison-Wesley.

[La00]
Langley, P. (2000). Crafting papers on machine learning. In *Proceedings
of the Seventeenth International Conference on Machine Learning*, Stanford,
CA, pp. 1207-1211. San Francisco, CA: Morgan Kaufmann Publishers. **(HTML
/ .ps.gz)**

[La02]
Langley, P. (2002). *Issues in Research Methodology*. Palo Alto, CA:
Institute for the Study of Learning and Expertise. Available from URL: http://www.isle.org/~langley/methodology.html.

**Recent and Current
Research**

[FGKP99]
Friedman, N., Getoor, L., Koller, D., & Pfeffer, A. (1999). Learning Probabilistic
Relational Models. In *Proceedings of the International Joint Conference
on Artificial Intelligence (IJCAI-1999)*,
Stockholm, SWEDEN. San Francisco, CA: Morgan Kaufmann Publishers. **(PDF)**

[GFTK02]
Getoor, L., Friedman, N., Koller, D., & Taskar, B. (2002). Learning Probabilistic
Models of Link Structure. *Journal of Machine Learning Research*, 3(2002):679-707.
**(PDF)**

[GH02]
Guo, H. & Hsu, W. H. (2002). A Survey of Algorithms for Real-Time Bayesian
Network Inference. In Guo, H., Horvitz, E., Hsu, W. H., and Santos, E., eds.
*Working Notes of the Joint Workshop (WS-18) on Real-Time Decision Support
and Diagnosis*, AAAI/UAI/KDD-2002. Edmonton, Alberta, CANADA, 29 July 2002.
Menlo Park, CA: AAAI Press. **(PDF)**

[Gu02]
Guo, H. (2002). A Bayesian Metareasoner for Algorithm Selection for Real-time
Bayesian Network Inference Problems (Doctoral Consortium Abstract). In *Proceedings
of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002)*,
Edmonton, Alberta, CANADA, p. 983. Menlo Park, CA: AAAI Press. **(PDF)**

[HGPS02]
Hsu, W. H., Guo, H., Perry, B. B., & Stilson, J. A. (2002). A permutation
genetic algorithm for variable ordering in learning Bayesian networks from data.
In *Proceedings of the Genetic **and
Evolutionary Computation Conference (GECCO-2002)*, New York, NY. San Francisco,
CA: Morgan Kaufmann Publishers. **(PDF
/ PostScript
/ .ps.gz)
- **

**Software**

[SGS04]
Spirtes, P. & Glymour, C. & Scheines, R. (2004). *The TETRAD Project: Causal Models and Statistical Data*. Pittsburgh, PA:
Carnegie Mellon University Department of Philosophy. Available from URL: http://www.phil.cmu.edu/projects/tetrad/.

[LBB+04]
Lauritzen, S. L. & Badsberg, J. H. & Bøttcher, S. G. & Dalgaard, P. & Dethlefsen, C. & Edwards, D. & Eriksen, P. S. & Gregersen, A. R. & Højsgaard, S. & Kreiner, S. (2004). *gR - Graphical models in R*. Aalborg, DENMARK:
Aalborg University Department of Mathematical Sciences. Available from URL: http://www.math.auc.dk/gr/.

[Mu04]
Murphy, K. P. (2004). *Bayes Net Toolbox v5 for MATLAB*. Cambridge, MA:
MIT Computer Science and Artificial Intelligence Laboratory. Available from URL: http://www.ai.mit.edu/~murphyk/Software/BNT/bnt.html.

[PS02]
Perry, B. P. & Stilson, J. A. (2002). *BN-Tools*: A Software Toolkit
for Experimentation in BBNs (Student Abstract). In *Proceedings of the Eighteenth
National Conference on Artificial Intelligence (AAAI-2002)*, Edmondon, Alberta,
CANADA, pp. 963-964. Menlo Park, CA: AAAI Press. **(PS)**

**Textbooks and Tutorials
**

[Mu01]
Murphy, K. P. (2001). *A Brief Introduction to Graphical Models and Bayesian
Networks*. Berkeley, CA: Department of Computer Science, University of California
- Berkeley. Available from URL: http://www.cs.berkeley.edu/~murphyk/Bayes/bayes.html.

[Ne90]
Neapolitan, R. E. (1990). *Probabilistic Reasoning in Expert Systems: Theory
and Applications*. New York, NY: Wiley-Interscience.**
(Out of print; Amazon.com
reference)**

[Ne03]
Neapolitan, R. E. (2003). *Learning Bayesian Networks*. Englewood Cliffs,
NJ: Prentice Hall.**
(Amazon.com
reference)**

**Foundational Material
and Seminal Research**

[CH92]
Cooper, G. F. & Herskovits, E. (1992). A Bayesian method for the induction
of probabilistic networks from data. *Machine Learning*, *9*(4):309-347.

[Jo98]
Jordan, M. I., *ed.* (1998). *Learning in Graphical Models.* Cambridge,
MA: MIT Press. **(Amazon.com
reference)**

[LS88]
Lauritzen, S., & Spiegelhalter, D. J. (1988). Local Computations with Probabilities
on Graphical Structures and Their Application to Expert Systems. *Journal
of the Royal Statistical Society Series B 50*:157-224.

[SGS01]
Spirtes, P. & Glymour, C. & Scheines, R. (2001). *Causation, Prediction, and Search, Second Edition*. Cambridge,
MA: MIT Press. **(Amazon.com
reference)**

**Theses and Dissertations
Related to BNJ**

[Me99]
Mengshoel, O. J. (1999). *Efficient Bayesian Network Inference: Genetic Algorthms,
Stochastic Local Search and Abstraction. *Ph.D. Dissertation, Department
of Computer Science, University of Illinois at Urbana-Champaign, May, 1999.
Available from URL: http://www-kbs.ai.uiuc.edu/web/kbs/publicLibrary/KBSPubs/Thesis/.

**Workshops Relevant
to BNJ**

[GHHS02]
Guo, H., Horvitz, E., Hsu, W. H., and Santos, E., eds. (2002). *Working Notes
of the Joint Workshop (WS-18) on Real-Time Decision Support and Diagnosis*,
AAAI/UAI/KDD-2002. Edmonton, Alberta, CANADA, 29 July 2002. Menlo Park, CA:
AAAI Press. Available from URL: http://www.kddresearch.org/Workshops/RTDSDS-2002.

[HJP03]
Hsu, W. H., Joehanes, R., & Page, C. D. (2003). *Working Notes of the
Workshop on Learning Graphical Models in Computational Genomics*, International
Joint Conference on Artificial Intelligence (IJCAI-2003). Acapulco, MEXICO,
09 Aug 2003. Available from URL: http://www.kddresearch.org/Workshops/IJCAI-2003-Bioinformatics.

*Page created: **Fri 20
Dec 2002*

*Last updated: Sun 06 Jun 2004*

*William H. Hsu*

*BNJ Development Team*