9. UAI 1993: Washington, DC, USA

• Marek J. Druzdzel, Herbert A. Simon:
  Causality in Bayesian Belief Networks. 3-11
  
• Judea Pearl:
  From Conditional Oughts to Qualitative Decision Theory. 12-22
  
• Russ B. Altman:
  A Probabilistic Algorithm for Calculating Structure: Borrowing from Simulated Annealing. 23-31
  
• Scott A. Musman, Li Wu Chang:
  A Study of Scaling Issues in Bayesian Belief Networks for Ship Classification. 32-39
  
• Gregory M. Provan:
  Tradeoffs in Constructing and Evaluating Temporal Influence Diagrams. 40-47
  
• Harold P. Lehmann, Ross D. Shachter:
  End-User Construction of Influence Diagrams for Bayesian Statistics. 48-54
  
• Steven M. LaValle, Seth Hutchinson:
  On Considering Uncertainty and Alternatives in Low-Level Vision. 55-63
  
• Paul Dagum, Adam Galper:
  Forecasting Sleep Apnea with Dynamic Network Models. 64-71
  
• Peter J. Regan:
  Normative Engineering Risk Management Systems. 72-79
  
• David Heckerman, Michael Shwe:
  Diagnosis of Multiple Faults: A Sensitivity Analysis. 80-90
  
• Paul Dagum, Adam Galper:
  Additive Belief-Network Models. 91-98
  
• Francisco Javier Díez:
  Parameter adjustment in Bayes networks. The generalized noisy OR-gate. 99-105
  
• Didier Dubois, Henri Prade:
  A fuzzy relation-based extension of Reggia's relational model for diagnosis handling uncertain and incomplete information. 106-113
  
• Morten Elvang-Gøransson, Paul Krause, John Fox:
  Dialectic reasoning with inconsistent information. 114-121
  
• David Heckerman:
  Causal Independence for Knowledge Acquisition and Inference. 122-127
  
• Eric Horvitz, Adrian C. Klein:
  Utility-Based Abstraction and Categorization. 128-135
  
• Kathryn B. Laskey:
  Sensitivity Analysis for Probability Assessments in Bayesian Networks. 136-142
  
• John F. Lemmer:
  Causal Modeling. 143-151
  
• Izhar Matzkevich, Bruce Abramson:
  Some Complexity Considerations in the Combination of Belief Networks. 152-158
  
• Izhar Matzkevich, Bruce Abramson:
  Deriving A Minimal itI-map of a Belief Network Relative to a Target Ordering of its Nodes. 159-165
  
• Kim-Leng Poh, Michael R. Fehling:
  Probabilistic Conceptual Network: A Belief Representation Scheme for Utility-Based Categorization. 166-173
  
• Kim-Leng Poh, Eric Horvitz:
  Reasoning about the Value of Decision-Model Refinement: Methods and Application. 174-182
  
• William B. Poland, Ross D. Shachter:
  Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous Uncertainties. 183-190
  
• Prakash P. Shenoy:
  Valuation Networks and Conditional Independence. 191-199
  
• Solomon Eyal Shimony:
  Relevant Explanations: Allowing Disjunctive Assignments. 200-207
  
• Sampath Srinivas:
  A Generalization of the Noisy-Or Model. 208-218
  
• Fahiem Bacchus:
  Using First-Order Probability Logic for the Construction of Bayesian Networks. 219-226
  
• Marie desJardins:
  Representing and Reasoning With Probabilistic Knowledge: A Bayesian Approach. 227-234
  
• John W. Egar, Mark A. Musen:
  Graph-Grammar Assistance for Automated Generation of Influence Diagrams. 235-242
  
• Wai Lam, Fahiem Bacchus:
  Using Causal Information and Local Measures to Learn Bayesian Networks. 243-250
  
• Ron Musick:
  Minimal Assumption Distribution Propagation in Belief Networks. 251-258
  
• Moninder Singh, Marco Valtorta:
  An Algorithm for the Construction of Bayesian Network Structures from Data. 259-265
  
• Joe Suzuki:
  A Construction of Bayesian Networks from Databases Based on an MDL Principle. 266-273
  
• Soe-Tsyr Yuan:
  Knowledge-Based Decision Model Construction for the Hierarchical Diagnosis: A Preliminary Report. 274-284
  
• Lisa J. Burnell:
  A Synthesis of Logical and Probabilistic Reasoning for Program Understanding and Debugging. 285-291
  
• Peter Che, Richard E. Neapolitan, James R. Kenevan, Martha W. Evens:
  An Implementation of a Method for Computing the Uncertainty in Inferred Probabilities in Belief Networks. 292-300
  
• Bruce D'Ambrosio:
  Incremental Probabilistic Inference. 301-308
  
• Thomas L. Dean, Leslie Pack Kaelbling, Jak Kirman, Ann E. Nicholson:
  Deliberation Scheduling for Time-Critical Sequential Decision Making. 309-316
  
• Marek J. Druzdzel, Max Henrion:
  Intercausal Reasoning with Uninstantiated Ancestor Nodes. 317-325
  
• Dan Geiger, David Heckerman:
  Inference Algorithms for Similarity Networks. 326-334
  
• Paul E. Lehner, Azar Sadigh:
  Two Procedures for Compiling Influence Diagrams. 335-341
  
• Zhaoyu Li, Bruce D'Ambrosio:
  An efficient approach for finding the MPE in belief networks. 342-349
  
• Todd Michael Mansell:
  A method for Planning Given Uncertain and Incomplete Information. 350-358
  
• David Poole:
  The use of conflicts in searching Bayesian networks. 359-367
  
• Carlos Rojas-Guzmán, Mark A. Kramer:
  GALGO: A Genetic ALGOrithm Decision Support Tool for Complex Uncertain Systems Modeled with Bayesian Belief Networks. 368-375
  
• Sumit Sarkar:
  Using Tree-Decomposable Structures to Approximate Belief Networks. 376-382
  
• Ross D. Shachter, Pierre Ndilikilikesha:
  Using Potential Influence Diagrams for Probabilistic Inference and Decision Making. 383-390
  
• Thomas Verma, Judea Pearl:
  Deciding Morality of Graphs is NP-complete. 391-399
  
• Nevin Lianwen Zhang, Runping Qi, David L. Poole:
  Incremental computation of the value of perfect information in stepwise-decomposable influence diagrams. 400-410
  
• Salem Benferhat, Didier Dubois, Henri Prade:
  Argumentative inference in uncertain and inconsistent knowledge bases. 411-419
  
• Adnan Darwiche:
  Argument Calculus and Networks. 420-427
  
• John Fox, Paul Krause, Morten Elvang-Gøransson:
  Argumentation as a General Framework for Uncertain Reasoning. 428-434
  
• Simon Parsons, E. H. Mamdani:
  On reasoning in networks with qualitative uncertainty. 435-442
  
• S. K. Michael Wong, Zhiwei Wang:
  Qualitative Measures of Ambiguity. 443-452
  
• Robert F. Bordley:
  A Bayesian Variant of Shafer's Commonalities For Modelling Unforeseen Events. 453-460
  
• Craig Boutilier:
  The Probability of a Possibility: Adding Uncertainty to Default Rules. 461-468
  
• Dimiter Driankov, Jérôme Lang:
  Possibilistic decreasing persistence. 469-476
  
• J. W. Guan, David A. Bell:
  Discounting and Combination Operations in Evidential Reasoning. 477-484
  
• Jürg Kohlas, Paul-André Monney:
  Probabilistic Assumption-Based Reasoning. 485-491
  
• Serafín Moral, Luis M. de Campos:
  Partially Specified Belief Functions. 492-499
  
• Philippe Smets:
  Jeffrey's rule of conditioning generalized to belief functions. 500-505
  
• Fengming Song, Ping Liang:
  Inference with Possibilistic Evidence. 506-514
  
• Carl G. Wagner, Bruce Tonn:
  Constructing Lower Probabilities. 515-518
  
• Pei Wang:
  Belief Revision in Probability Theory. 519-526
  
• Nic Wilson:
  The Assumptions Behind Dempster's Rule. 527-534
  
• Hong Xu, Yen-Teh Hsia, Philippe Smets:
  A Belief-Function Based Decision Support System. 535-542
  

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