Table of Contents

• Causality in Bayesian Belief NetworksMarek J. Druzdzel, Herbert A. Simon. 3-11 [doi]
• From Conditional Oughts to Qualitative Decision TheoryJudea Pearl. 12-22 [doi]
• A Probabilistic Algorithm for Calculating Structure: Borrowing from Simulated AnnealingRuss B. Altman. 23-31 [doi]
• A Study of Scaling Issues in Bayesian Belief Networks for Ship ClassificationScott A. Musman, Li Wu Chang. 32-39 [doi]
• Tradeoffs in Constructing and Evaluating Temporal Influence DiagramsGregory M. Provan. 40-47 [doi]
• End-User Construction of Influence Diagrams for Bayesian StatisticsHarold P. Lehmann, Ross D. Shachter. 48-54 [doi]
• On Considering Uncertainty and Alternatives in Low-Level VisionSteven M. LaValle, Seth Hutchinson. 55-63 [doi]
• Forecasting Sleep Apnea with Dynamic Network ModelsPaul Dagum, Adam Galper. 64-71 [doi]
• Normative Engineering Risk Management SystemsPeter J. Regan. 72-79 [doi]
• Diagnosis of Multiple Faults: A Sensitivity AnalysisDavid Heckerman, Michael Shwe. 80-90 [doi]
• Additive Belief-Network ModelsPaul Dagum, Adam Galper. 91-98 [doi]
• Parameter adjustment in Bayes networks. The generalized noisy OR-gateFrancisco Javier Díez. 99-105 [doi]
• A fuzzy relation-based extension of Reggia s relational model for diagnosis handling uncertain and incomplete informationDidier Dubois, Henri Prade. 106-113 [doi]
• Dialectic reasoning with inconsistent informationMorten Elvang-Gøransson, Paul Krause, John Fox. 114-121 [doi]
• Causal Independence for Knowledge Acquisition and InferenceDavid Heckerman. 122-127 [doi]
• Utility-Based Abstraction and CategorizationEric Horvitz, Adrian Klein. 128-135 [doi]
• Sensitivity Analysis for Probability Assessments in Bayesian NetworksKathryn B. Laskey. 136-142 [doi]
• Causal ModelingJohn F. Lemmer. 143-151 [doi]
• Some Complexity Considerations in the Combination of Belief NetworksIzhar Matzkevich, Bruce Abramson. 152-158 [doi]
• Deriving A Minimal itI-map of a Belief Network Relative to a Target Ordering of its NodesIzhar Matzkevich, Bruce Abramson. 159-165 [doi]
• Probabilistic Conceptual Network: A Belief Representation Scheme for Utility-Based CategorizationKim-Leng Poh, Michael R. Fehling. 166-173 [doi]
• Reasoning about the Value of Decision-Model Refinement: Methods and ApplicationKim-Leng Poh, Eric Horvitz. 174-182 [doi]
• Mixtures of Gaussians and Minimum Relative Entropy Techniques for Modeling Continuous UncertaintiesWilliam B. Poland, Ross D. Shachter. 183-190 [doi]
• Valuation Networks and Conditional IndependencePrakash P. Shenoy. 191-199 [doi]
• Relevant Explanations: Allowing Disjunctive AssignmentsSolomon Eyal Shimony. 200-207 [doi]
• A Generalization of the Noisy-Or ModelSampath Srinivas. 208-218 [doi]
• Using First-Order Probability Logic for the Construction of Bayesian NetworksFahiem Bacchus. 219-226 [doi]
• Representing and Reasoning With Probabilistic Knowledge: A Bayesian ApproachMarie desJardins. 227-234 [doi]
• Graph-Grammar Assistance for Automated Generation of Influence DiagramsJohn W. Egar, Mark A. Musen. 235-242 [doi]
• Using Causal Information and Local Measures to Learn Bayesian NetworksWai Lam, Fahiem Bacchus. 243-250 [doi]
• Minimal Assumption Distribution Propagation in Belief NetworksRon Musick. 251-258 [doi]
• An Algorithm for the Construction of Bayesian Network Structures from DataMoninder Singh, Marco Valtorta. 259-265 [doi]
• A Construction of Bayesian Networks from Databases Based on an MDL PrincipleJoe Suzuki. 266-273 [doi]
• Knowledge-Based Decision Model Construction for the Hierarchical Diagnosis: A Preliminary ReportSoe-Tsyr Yuan. 274-284 [doi]
• A Synthesis of Logical and Probabilistic Reasoning for Program Understanding and DebuggingLisa J. Burnell. 285-291 [doi]
• An Implementation of a Method for Computing the Uncertainty in Inferred Probabilities in Belief NetworksPeter Che, Richard E. Neapolitan, James R. Kenevan, Martha W. Evens. 292-300 [doi]
• Incremental Probabilistic InferenceBruce D Ambrosio. 301-308 [doi]
• Deliberation Scheduling for Time-Critical Sequential Decision MakingThomas Dean, Leslie Pack Kaelbling, Jak Kirman, Ann E. Nicholson. 309-316 [doi]
• Intercausal Reasoning with Uninstantiated Ancestor NodesMarek J. Druzdzel, Max Henrion. 317-325 [doi]
• Inference Algorithms for Similarity NetworksDan Geiger, David Heckerman. 326-334 [doi]
• Two Procedures for Compiling Influence DiagramsPaul E. Lehner, Azar Sadigh. 335-341 [doi]
• An efficient approach for finding the MPE in belief networksZhaoyu Li, Bruce D Ambrosio. 342-349 [doi]
• A method for Planning Given Uncertain and Incomplete InformationTodd Michael Mansell. 350-358 [doi]
• The use of conflicts in searching Bayesian networksDavid Poole. 359-367 [doi]
• GALGO: A Genetic ALGOrithm Decision Support Tool for Complex Uncertain Systems Modeled with Bayesian Belief NetworksCarlos Rojas-Guzmán, Mark A. Kramer. 368-375 [doi]
• Using Tree-Decomposable Structures to Approximate Belief NetworksSumit Sarkar. 376-382 [doi]
• Using Potential Influence Diagrams for Probabilistic Inference and Decision MakingRoss D. Shachter, Pierre Ndilikilikesha. 383-390 [doi]
• Deciding Morality of Graphs is NP-completeThomas Verma, Judea Pearl. 391-399 [doi]
• Incremental computation of the value of perfect information in stepwise-decomposable influence diagramsNevin Lianwen Zhang, Runping Qi, David Poole. 400-410 [doi]
• Argumentative inference in uncertain and inconsistent knowledge basesSalem Benferhat, Didier Dubois, Henri Prade. 411-419 [doi]
• Argument Calculus and NetworksAdnan Darwiche. 420-427 [doi]
• Argumentation as a General Framework for Uncertain ReasoningJohn Fox, Paul Krause, Morten Elvang-Gøransson. 428-434 [doi]
• On reasoning in networks with qualitative uncertaintySimon Parsons, E. H. Mamdani. 435-442 [doi]
• Qualitative Measures of AmbiguityS. K. Michael Wong, Zhiwei Wang. 443-452 [doi]
• A Bayesian Variant of Shafer s Commonalities For Modelling Unforeseen EventsRobert F. Bordley. 453-460 [doi]
• The Probability of a Possibility: Adding Uncertainty to Default RulesCraig Boutilier. 461-468 [doi]
• Possibilistic decreasing persistenceDimiter Driankov, Jérôme Lang. 469-476 [doi]
• Discounting and Combination Operations in Evidential ReasoningJ. W. Guan, David A. Bell. 477-484 [doi]
• Probabilistic Assumption-Based ReasoningJürg Kohlas, Paul-André Monney. 485-491 [doi]
• Partially Specified Belief FunctionsSerafín Moral, Luis M. de Campos. 492-499 [doi]
• Jeffrey s rule of conditioning generalized to belief functionsPhilippe Smets. 500-505 [doi]
• Inference with Possibilistic EvidenceFengming Song, Ping Liang. 506-514 [doi]
• Constructing Lower ProbabilitiesCarl G. Wagner, Bruce Tonn. 515-518 [doi]
• Belief Revision in Probability TheoryPei Wang. 519-526 [doi]
• The Assumptions Behind Dempster s RuleNic Wilson. 527-534 [doi]
• A Belief-Function Based Decision Support SystemHong Xu, Yen-Teh Hsia, Philippe Smets. 535-542 [doi]