Abstract is missing.
- Models vs inductive inference for dealing with probabilistic knowledgeNorman C. Dalkey. 3-10 [doi]
- An axiomatic framework for belief updatesDavid Heckerman. 11-22 [doi]
- The myth of modularity in rule-based systems for reasoning with uncertaintyDavid Heckerman, Eric Horvitz. 23-34 [doi]
- Imprecise meanings as a cause of uncertainty in medical knowledge-based systemsSteven J. Henkind. 35-42 [doi]
- Evidence as opinions of expertsRobert A. Hummel, Michael S. Landy. 43-54 [doi]
- Probabilistic logic: some comments and possible use for nonmonotonic reasoningMary McLeish. 55-62 [doi]
- Experiments with interval-valued uncertaintyRichard M. Tong, Lee A. Appelbaum. 63-76 [doi]
- Evaulation of uncertain inference models I: PROSPECTORRobert M. Yadrick, Bruce M. Perrin, David S. Vaughan, Peter D. Holden, Karl G. Kempf. 77-88 [doi]
- Experimentally comparing uncertain inference systems to probabilityBen P. Wise. 89-102 [doi]
- Knowledge engineering within a generalised bayesian frameworkStephen W. Barth, Steven W. Norton. 103-114 [doi]
- Learning to predict: an inductive approachKaihu Chen. 115-124 [doi]
- Towards a general-purpose belief maintenance systemBrian Falkenhainer. 125-132 [doi]
- A non-iterative maximum entropy algorithmSally A. Goldman, Ronald L. Rivest. 133-148 [doi]
- Propagating uncertainty in bayesian networks by probabilistic logic samplingMax Henrion. 149-164 [doi]
- An explanation mechanism for bayesian inferencing systemsSteven W. Norton. 165-174 [doi]
- On the rational scope of probabilistic rule-based inference systemsShimon Schocken. 175-190 [doi]
- DAVID: influence diagram processing system for the macintoshRoss D. Shachter. 191-196 [doi]
- Qualitativce probabilistic networks for planning under uncertaintyMichael P. Wellman. 197-208 [doi]
- On implementing usual valuesRonald R. Yager. 209-220 [doi]
- Some extensions of probabilistic logicSu-Shing Chen. 221-228 [doi]
- Belief as summarization and meta-supportA. Julian Craddock, Roger A. Browse. 229-236 [doi]
- Non-monotonicity in probabilistic reasoningBenjamin N. Grosof. 237-250 [doi]
- A semantic approach to non-monotonic entailmentsJames Hawthorne. 251-262 [doi]
- KnowledgeHenry E. Kyburg Jr.. 263-272 [doi]
- Computing reference classesRonald Prescott Loui. 273-290 [doi]
- Distributedrevision of belief commitment in composite explanationsJudea Pearl. 291-316 [doi]
- A backwards view for assessmentRoss D. Shachter, David Heckerman. 317-324 [doi]
- Propagation of belief functions: a distributed approachPrakash P. Shenoy, Glenn Shafer, Khaled Mellouli. 325-336 [doi]
- Generalising fuzzy logic probabilistic inferencesSilvio Ursic. 337-364 [doi]
- The sum-and-lattice-points method based on an evidential-reasoning system applied to the real-time vehicle guidance problemShoshana Abel. 365-370 [doi]
- Probabilistic reasoning about ship imagesLashon B. Booker, Naveen Hota. 371-380 [doi]
- Information and multi-sensor coordinationGregory D. Hager, Hugh F. Durrant-Whyte. 381-394 [doi]
- Planning, scheduling and uncertainty in the sequence of future eventsB. R. Fox, Karl G. Kempf. 395-402 [doi]
- Evidential reasoning in a computer vision systemZe-Nian Li, Leonard Uhr. 403-412 [doi]
- Bayesian inference for radar imagery based surveillanceTod S. Levitt. 413-422 [doi]
- A causal bayesian model for the diagnosis of appendicitisStanley M. Schwartz, Jonathan Baron, John R. Clarke. 423-434 [doi]
- Estimating uncertain spatial relationships in roboticsRandall Smith, Matthew Self, Peter Cheeseman. 435-461 [doi]