Table of Contents

• RES: A Relative Method for Evidential ReasoningZhi An, David A. Bell, John G. Hughes. 1-8 [doi]
• Optimizing Causal Orderings for Generating DAGs from DataRemco R. Bouckaert. 9-16 [doi]
• Modal Logics for Qualitative Possibility and BeliefsCraig Boutilier. 17-24 [doi]
• Structural Controllability and Observability in Influence DiagramsBrian Y. Chan, Ross D. Shachter. 25-32 [doi]
• Lattice-based Graded Logic: A Multimodal ApproachPhilippe Chatalic, Christine Froidevaux. 33-40 [doi]
• Dynamic Network Models for ForecastingPaul Dagum, Adam Galper, Eric Horvitz. 41-48 [doi]
• Reformulating Inference Problems Through Selective ConditioningPaul Dagum, Eric Horvitz. 49-54 [doi]
• Entropy and Belief NetworksNorman C. Dalkey. 55-58 [doi]
• Parallelizing Probabilistic Inference: Some Early ExplorationsBruce D Ambrosio, Tony Fountain, Zhaoyu Li. 59-66 [doi]
• Objection-based Causal Exception NetworksAdnan Darwiche. 67-73 [doi]
• A Symbolic Approach to Reasoning with Linguistic QuantifiersDidier Dubois, Henri Prade, Lluis Godo, Ramon López de Mántaras. 74-82 [doi]
• Possibilistic Assumption based Truth Maintenance System, Validation in a Data Fusion ApplicationFrancesco Fulvio Monai, Thomas Chehire. 83-91 [doi]
• An Entropy-based Learning Algorithm of Bayesian Conditional TreesDan Geiger. 92-97 [doi]
• Knowledge integration for Conditional Probability AssessmentsAngelo Gilio, Fulvio Spezzaferri. 98-103 [doi]
• Integrating Model Construction and EvaluationRobert P. Goldman, Jack S. Breese. 104-111 [doi]
• Reasoning with Qualitative Probabilities Can Be TractableMoisés Goldszmidt, Judea Pearl. 112-120 [doi]
• A Computational Scheme for Reasoning in Dynamic Probabilistic NetworksUffe Kjærulff. 121-129 [doi]
• The Dynamic of Belief in the Transferable Belief Model and Specialization-Generalization MatricesFrank Klawonn, Philippe Smets. 130-137 [doi]
• A Note on the Measure of DiscordGeorge J. Klir, Behzad Parviz. 138-141 [doi]
• Semantics for Probabilistic InferenceHenry E. Kyburg Jr.. 142-148 [doi]
• Some Problems for Convex BayesiansHenry E. Kyburg Jr., Michael Pittarelli. 149-154 [doi]
• Bayesian Meta-Reasoning: Determining Model Adequacy from within a Small WorldKathryn B. Laskey. 155-158 [doi]
• The Bounded BayesianKathryn B. Laskey. 159-165 [doi]
• Representing Context-Sensitive Knowledge in a Network Formalism: A Preliminary ReportTze-Yun Leong. 166-173 [doi]
• A Probabilistic Network of PredicatesDekang Lin. 174-181 [doi]
• Representing Heuristic Knowledge in D-S TheoryWeiru Liu, John G. Hughes, Michael F. McTear. 182-190 [doi]
• The Topological Fusion of Bayes NetsIzhar Matzkevich, Bruce Abramson. 191-198 [doi]
• Calculating Uncertainty Intervals from Conditional Convex Sets of ProbabilitiesSerafín Moral. 199-206 [doi]
• Sensor Validation Using Dynamic Belief NetworksAnn E. Nicholson, J. Michael Brady. 207-214 [doi]
• Empirical Probabilities in Monadic Deductive DatabasesRaymond T. Ng, V. S. Subrahmanian. 215-222 [doi]
• aHUGIN: A System Creating Adaptive Causal Probabilistic NetworksKristian G. Olesen, Steffen L. Lauritzen, Finn Verner Jensen. 223-229 [doi]
• MESA: Maximum Entropy by Simulated AnnealingGerhard Paass. 230-237 [doi]
• Decision Methods for Adaptive Task-Sharing in Associate SystemsThomas S. Paterson, Michael R. Fehling. 238-243 [doi]
• Modeling Uncertain Temporal Evolutions in Model-based DiagnosisLuigi Portinale. 244-251 [doi]
• Guess-and-Verify Heuristics for Reducing Uncertainties in Expert Classification SystemsYuping Qiu, Louis Anthony Cox Jr., Lawrence Davis. 252-258 [doi]
• R&D Analyst: An Interactive Approach to Normative Decision System Model ConstructionPeter J. Regan, Samuel Holtzman. 259-267 [doi]
• Possibilistic Constraint Satisfaction Problems or How to Handle Soft Constraints? Thomas Schiex. 268-275 [doi]
• Decision Making Using Probabilistic Inference MethodsRoss D. Shachter, Mark A. Peot. 276-283 [doi]
• Conditional lndependence in Uncertainty TheoriesPrakash P. Shenoy. 284-291 [doi]
• The Nature of the Unnormalized Beliefs Encountered in the Transferable Belief ModelPhilippe Smets. 292-297 [doi]
• Intuitions about Ordered Beliefs Leading to Probabilistic ModelsPaul Snow. 298-302 [doi]
• Expressing Relational and Temporal Knowledge in Visual Probabilistic NetworksLuis Enrique Sucar, Duncan Fyfe Gillies. 303-309 [doi]
• A Fuzzy Logic Approach to Target TrackingChin-Wang Tao, Wiley E. Thompson. 310-314 [doi]
• Towards Precision of Probabilistic Bounds PropagationHelmut Thöne, Ulrich Güntzer, Werner Kießling. 315-322 [doi]
• An Algorithm for Deciding if a Set of Observed Independencies Has a Causal ExplanationThomas Verma, Judea Pearl. 323-330 [doi]
• Generalizing Jeffrey ConditionalizationCarl G. Wagner. 331-335 [doi]
• Interval Structure: A Framework for Representing Uncertain InformationS. K. Michael Wong, Lusheng Wang, Yiyu Yao. 336-343 [doi]
• Exploring Localization in Bayesian Networks for Large Expert SystemsYang Xiang, David Poole, Michael P. Beddoes. 344-351 [doi]
• A Decision Calculus for Belief Functions in Valuation-based SystemsHong Xu. 352-359 [doi]