Uncertainty and Vagueness in Knowledge Based Systems

[1]  H Raiffa,et al.  Decision Analysis: Introductory Lectures on Choices under Uncertainty. , 1969 .

[2]  Philippe Smets,et al.  Resolving misunderstandings about belief functions , 1992, Int. J. Approx. Reason..

[3]  Philippe Smets,et al.  Varieties of ignorance and the need for well-founded theories , 1991, Inf. Sci..

[4]  Frank Klawonn,et al.  On a Tool for Reasoning with Mass Distributions , 1991, IJCAI.

[5]  Prakash P. Shenoy,et al.  Valuation-based systems for propositional logic , 1991 .

[6]  J. M. Larrazabal,et al.  Reasoning about change , 1991 .

[7]  Richard E. Neapolitan,et al.  Probabilistic reasoning in expert systems - theory and algorithms , 2012 .

[8]  R. Kruse,et al.  SPECIALIZATION—A NEW CONCEPT FOR UNCERTAINTY HANDLING WITH BELIEF FUNCTIONS , 1990 .

[9]  N. Wermuth,et al.  On Substantive Research Hypotheses, Conditional Independence Graphs and Graphical Chain Models , 1990 .

[10]  Judea Pearl,et al.  Reasoning with belief functions: An analysis of compatibility , 1990, Int. J. Approx. Reason..

[11]  David J. Spiegelhalter,et al.  Sequential updating of conditional probabilities on directed graphical structures , 1990, Networks.

[12]  Judea Pearl,et al.  Equivalence and Synthesis of Causal Models , 1990, UAI.

[13]  Prakash P. Shenoy.  Valuation-based systems for discrete optimisation , 1990, UAI.

[14]  Rudolf Kruse,et al.  On the Combination of Information Sources , 1990, IPMU.

[15]  I. Graham.  Non-standard logics for automated reasoning , 1990 .

[16]  Glenn Shafer,et al.  Readings in Uncertain Reasoning , 1990 .

[17]  Pekka Orponen,et al.  Dempster's Rule of Combination is #P-Complete , 1990, Artif. Intell..

[18]  Michael P. Wellman.  Qualitative Probabilistic Networks for Planning Under Uncertainty , 1990, UAI 1990.

[19]  Bernhard Nebel,et al.  Reasoning and Revision in Hybrid Representation Systems , 1990, Lecture Notes in Computer Science.

[20]  Kurt Weichselberger,et al.  A Methodology for Uncertainty in Knowledge-Based Systems , 1990, Lecture Notes in Computer Science.

[21]  Rudolf Kruse,et al.  Fuzzy reasoning in a multidimensional space of hypotheses , 1990, Int. J. Approx. Reason..

[22]  Ramon López de Mántaras,et al.  Approximate Reasoning Models , 1990 .

[23]  David J. Spiegelhalter,et al.  Assessment, Criticism and Improvement of Imprecise Subjective Probabilities for a Medical Expert System , 2013, UAI.

[24]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[25]  Eric Neufeld,et al.  Defaults and Probabilities; Extensions and Coherence , 1989, KR.

[26]  Rina Dechter,et al.  Learning structure from data: a survey , 1989, COLT '89.

[27]  Ronald R. Yager,et al.  On the Representation of Commonsense Knowledge by Possibilistic Reasoning , 1989, Int. J. Man Mach. Stud..

[28]  Kathryn B. Laskey,et al.  Assumptions, Beliefs and Probabilities , 1989, Artif. Intell..

[29]  Steen Andreassen,et al.  A munin network for the median nerve - a case study on loops , 1989, Appl. Artif. Intell..

[30]  Prakash P. Shenoy,et al.  A valuation-based language for expert systems , 1989, Int. J. Approx. Reason..

[31]  B. Planchet.  Credibility and conditioning , 1989 .

[32]  J. Q. Smith.  Influence Diagrams for Statistical Modelling , 1989 .

[33]  D. Saunders.  Improvements to INFERNO , 1989 .

[34]  John Yen,et al.  GERTIS: a Dempster-Shafer approach to diagnosing hierarchical hypotheses , 1989, CACM.

[35]  Kathryn B. Laskey,et al.  Representing and eliciting knowledge about uncertain evidence and its implications , 1989, IEEE Trans. Syst. Man Cybern..

[36]  David A. Lane.  Subjective probability and causality assessment , 1989 .

[37]  N. Wermuth,et al.  Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative , 1989 .

[38]  Philippe Smets,et al.  Epistemic necessity, possibility, and truth. Tools for dealing with imprecision and uncertainty in fuzzy knowledge-based systems , 1989, Int. J. Approx. Reason..

[39]  M. Stein.  Estimating and choosing , 1989 .

[40]  Marcus Spies.  Syllogistic inference under uncertainty , 1989 .

[41]  M. Smithson.  Ignorance and Uncertainty , 1989, Cognitive Science.

[42]  Michael Reinfrank,et al.  Non-Monotonic Reasoning , 1989, Lecture Notes in Computer Science.

[43]  Philippe Smets,et al.  Constructing the Pignistic Probability Function in a Context of Uncertainty , 1989, UAI.

[44]  Alexander S. Yeh.  Predicting the likely behaviours of continuous nonlinear systems in equilibrium , 1988, UAI.

[45]  Judea Pearl,et al.  Causal networks: semantics and expressiveness , 2013, UAI.

[46]  Spencer Star.  Generating decision structures and causal explanations for decision making , 1988, UAI.

[47]  Wolfgang Spohn,et al.  A general non-probabilistic theory of inductive reasoning , 2013, UAI.

[48]  Prakash P. Shenoy,et al.  An Axiomatic Framework for Bayesian and Belief-function Propagation , 2013, UAI 1988.

[49]  Ross D. Shachter.  A linear approximation method for probabilistic inference , 2013, UAI.

[50]  Eric Neufeld,et al.  Probabilsitic semantics and defaults , 2013, UAI.

[51]  Tod S. Levitt,et al.  Utility-based control for computer vision , 2013, UAI.

[52]  Henry E. Kyburg.  Epistemological relevance and statistical knowledge , 1988, UAI.

[53]  Chris Carter,et al.  Multiple decision trees , 2013, UAI.

[54]  David J. Spiegelhalter,et al.  Local computations with probabilities on graphical structures and their application to expert systems , 1990 .

[55]  Glenn Shafer,et al.  Evidential Reasoning Using DELEF , 1988, AAAI.

[56]  Prakash P. Shenoy,et al.  Axioms for probability and belief-function proagation , 1990, UAI.

[57]  Gary James Jason,et al.  The Logic of Scientific Discovery , 1988 .

[58]  J. Pearl.  On probability intervals , 1988, Int. J. Approx. Reason..

[59]  Ross D. Shachter.  Probabilistic Inference and Influence Diagrams , 1988, Oper. Res..

[60]  Alexander Gammerman,et al.  A Hybrid Approach to Deductive Uncertain Inference , 1988, Int. J. Man Mach. Stud..

[61]  Chia-Hoang Lee.  A Comparison of Two Evidential Reasoning Schemes , 1988, Artif. Intell..

[62]  Judea Pearl,et al.  On logic and probability , 1988, Comput. Intell..

[63]  Ross D. Shachter.  Efficient inference on generalized fault diagrams , 1988, Int. J. Approx. Reason..

[64]  Ben P. Wise.  Satisfaction of assumptions is a weak predictor of performance , 1987, Int. J. Approx. Reason..

[65]  John Yen.  Can evidence Be combined in the Dempster-shafer theory? , 1987, Int. J. Approx. Reason..

[66]  David S. Vaughan,et al.  Evaluation of Uncertain Inference Models I: Prospector* *This research was conducted under the McDonnell Douglas Independent, Research and Development program. , 1988 .

[67]  Glenn Shafer,et al.  Decision Making: LANGUAGES AND DESIGNS FOR PROBABILITY JUDGEMENT , 1988 .

[68]  Peter Szolovits,et al.  Artificial intelligence in medical diagnosis. , 1988, Annals of internal medicine.

[69]  Ronald Prescott Loui.  Evidential reasoning compared in a network usage prediction testbed: preliminary report , 1988, UAI.

[70]  Wilson X. Wen.  Minimum cross entropy reasoning in recursive causal networks , 1988, UAI.

[71]  Henry E. Kyburg,et al.  Probabilistic inference and non-monotonic inference , 1988, UAI.

[72]  John Yen,et al.  A framework of fuzzy evidential reasoning , 1988, UAI.

[73]  Glenn Shafer,et al.  Implementing Dempster's Rule for Hierarchical Evidence , 1987, Artif. Intell..

[74]  Philippe Smets,et al.  Implication in fuzzy logic , 1987, Int. J. Approx. Reason..

[75]  Khaled Mellouli,et al.  Propagating belief functions in qualitative Markov trees , 1987, Int. J. Approx. Reason..

[76]  Judea Pearl,et al.  Distributed Revision of Composite Beliefs , 1987, Artif. Intell..

[77]  Enrique H. Ruspini,et al.  Epistemic Logics, Probability, and the Calculus of Evidence , 1987, IJCAI.

[78]  Mary McLeish.  Nilsson's Probabilistic Entailment Extended to Dempster-Shafer Theory , 1987, UAI.

[79]  Thomas B. Slack.  Advantages and a limitation of using LEG nets in a real-time problem , 1987, Int. J. Approx. Reason..

[80]  Spencer Star,et al.  Theory-based inductive learning: An integration of symbolic and quantitative methods , 1987, Int. J. Approx. Reason..

[81]  Ross D. Shachter,et al.  A heuristic Bayesian approach to knowledge acquisition: Application to analysis of tissue-type plasminogen activator , 1987, Int. J. Approx. Reason..

[82]  Judea Pearl,et al.  The recovery of causal poly-trees from statistical data , 1987, Int. J. Approx. Reason..

[83]  John Yen.  Implementing evidential reasoning in expert systems , 1988, Int. J. Approx. Reason..

[84]  Lei Xu,et al.  Structuring causal tree models with continuous variables , 1987, Int. J. Approx. Reason..

[85]  Henry E. Kyburg,et al.  Higher order probabilities , 1987, Int. J. Approx. Reason..

[86]  Alessandro Saffiotti,et al.  An AI view of the treatment of uncertainty , 1987, The Knowledge Engineering Review.

[87]  Judea Pearl,et al.  Evidential Reasoning Using Stochastic Simulation of Causal Models , 1987, Artif. Intell..

[88]  E. Ruspini.  The Logical Foundations of Evidential Reasoning (revised) , 1987 .

[89]  Lotfi A. Zadeh,et al.  Approximate Reasoning in Intelligent Systems, Decision and Control , 1987 .

[90]  R. Yager.  On the dempster-shafer framework and new combination rules , 1987, Inf. Sci..

[91]  H. Kyburg.  Bayesian and Non-Bayesian Evidential Updating , 1987, Artif. Intell..

[92]  David Lindley,et al.  The Probability Approach to the Treatment of Uncertainty in Artificial Intelligence and Expert Systems , 1987 .

[93]  Augustine Kong,et al.  [Probabilistic Expert Systems in Medicine: Practical Issues in Handling Uncertainty]: Comment , 1987 .

[94]  R. Kruse,et al.  Statistics with vague data , 1987 .

[95]  Khaled Mellouli,et al.  On the propagation of beliefs in networks using the Dempster-Shafer theory of evidence , 1987 .

[96]  L. Zadeh,et al.  Fuzzy sets and applications : selected papers , 1987 .

[97]  David J. Spiegelhalter,et al.  A Unified Approach to Imprecision and Sensitivity of Beliefs in Expert Systems , 1987, Conference on Uncertainty in Artificial Intelligence.

[98]  David S. Vaughan,et al.  Evaluation of Uncertain Inference Models III: The Role of Tuning , 1987, UAI.

[99]  R R Yager,et al.  Using Approximate Reasoning to Represent Default Knowledge , 1987, Artif. Intell..

[100]  Judea Pearl,et al.  On Evidential Reasoning in a Hierarchy of Hypotheses , 1990, Artif. Intell..

[101]  John D. Lowrance,et al.  A Framework for Evidential-Reasoning Systems , 1990, AAAI.

[102]  Judea Pearl,et al.  Probabilistic reasoning using graphs , 1987, International Conference on Information Processing and Management of Uncertainty.

[103]  Shimon Schocken,et al.  On the Rational Scope of Probabilistic Rule-Based Inference Systems , 1987, UAI.

[104]  Ronald R. Yager,et al.  The entailment principle for dempster—shafer granules , 1986, Int. J. Intell. Syst..

[105]  Ross D. Shachter.  Evaluating Influence Diagrams , 1986, Oper. Res..

[106]  David J. Spiegelhalter.  Computers, Expert Systems, and ADRs: Can Causality Assessment Be Automated? , 1986 .

[107]  Glenn Shafer,et al.  The combination of evidence , 1986, Int. J. Intell. Syst..

[108]  Prakash P. Shenoy,et al.  Propagating Belief Functions with Local Computations , 1986, IEEE Expert.

[109]  Judea Pearl,et al.  Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..

[110]  W. Edwards,et al.  Decision Analysis and Behavioral Research , 1986 .

[111]  John Yen,et al.  A Reasoning Model Based on an Extended Dempster-Shafer Theory , 1986, AAAI.

[112]  L. Zadeh,et al.  On the combinability of evidence in the Dempster-Shafer theory , 1986, UAI 1986.

[113]  Ronald R. Yager,et al.  On implementing usual values , 1986, UAI.

[114]  Ben P. Wise.  Experimentally comparing uncertain inference systems to probability , 1986, UAI.

[115]  Silvio Ursic,et al.  Generalising fuzzy logic probabilistic inferences , 1986, UAI.

[116]  Khaled Mellouli,et al.  Propagation of belief functions: a distributed approach , 1986, UAI.

[117]  Ross D. Shachter.  DAVID: influence diagram processing system for the macintosh , 1986, UAI.

[118]  Ross D. Shachter,et al.  A backwards view for assessment , 1986, UAI.

[119]  Jonathan Baron,et al.  A causal bayesian model for the diagnosis of appendicitis , 1986, UAI.

[120]  Steven W. Norton.  An explanation mechanism for bayesian inferencing systems , 1986, UAI.

[121]  Ronald Prescott Loui.  Computing reference classes , 1986, UAI.

[122]  Tod S. Levitt.  Bayesian inference for radar imagery based surveillance , 1986, UAI.

[123]  Gerardo Steve.  Probabilistic inferential engines in expert systems: how should the strength of rules be expressed , 1986, IPMU.

[124]  Henry E. Kyburg,et al.  Representing knowledge and evidence for decision , 1986, IPMU.

[125]  D. Spiegelhalter.  A statistical view of uncertainty in expert systems , 1986 .

[126]  Pei-Zhuang Wang,et al.  Set-valued statistics and its application to earthquake engineering , 1986 .

[127]  Lotfi A. Zadeh,et al.  A Simple View of the Dempster-Shafer Theory of Evidence and Its Implication for the Rule of Combination , 1985, AI Mag..

[128]  C. V. Negoiţă,et al.  Fuzzy logic in knowledge engineering , 1986 .

[129]  Ze-Nian Li,et al.  Evidential reasoning in a computer vision system , 1986, UAI.

[130]  Judea Pearl,et al.  Distributedrevision of belief commitment in composite explanations , 1986, UAI.

[131]  Richard M. Tong,et al.  Experiments with interval-valued uncertainty , 1986, UAI.

[132]  Mary McLeish,et al.  Probabilistic Logic: Some Comments and Possible use for Nonmonotonic Reasoning , 1988, UAI 1988.

[133]  Ronald Prescott Loui,et al.  Interval-Based Decisions for Reasoning Systems , 2013, UAI.

[134]  Lotfi A. Zadeh,et al.  Syllogistic reasoning in fuzzy logic and its application to usuality and reasoning with dispositions , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[135]  Ronald R. Yager,et al.  Reasoning with Uncertainty for Expert Systems , 1985, IJCAI.

[136]  Lokendra Shastri,et al.  Evidential Reasoning in Semantic Networks: A Formal Theory , 1985, IJCAI.

[137]  Gerald Liu,et al.  Knowledge Structures and Evidential Reasoning in Decision Analysis , 1985, UAI.

[138]  Ross D. Shachter.  Intelligent Probabilistic Inference , 1985, UAI.

[139]  Dana S. Nau,et al.  An Evaluation of Two Alternatives to Minimax , 1985, UAI.

[140]  David S. Vaughan,et al.  An Odds Ratio Based Inference Engine , 1985, UAI.

[141]  Larry A. Rendell,et al.  Induction, of and by Probability , 1985, UAI.

[142]  Max Henrion,et al.  A Framework for Comparing Uncertain Inference Systems to Probability , 1985, UAI.

[143]  Ray J. Solomonoff,et al.  The Application of Algorithmic Probability to Problems in Artificial Intelligence , 1985, UAI.

[144]  John E. Shore,et al.  Relative Entropy, Probabilistic Inference, and AI , 1985, UAI.

[145]  Judea Pearl,et al.  A Constraint-Propagation Approach to Probabilistic Reasoning , 1985, UAI.

[146]  Henri Prade,et al.  Corrections to "A Computational Approach to Approximate and Plausible Reasoning with Applications to Expert Systems" , 1985, IEEE Trans. Pattern Anal. Mach. Intell..

[147]  King-Sun Fu,et al.  An Inexact Inference for Damage Assessment of Existing Structures , 1985, Int. J. Man Mach. Stud..

[148]  Henri Prade,et al.  On the Problems of Representation and Propagation of Uncertainty in Expert Systems , 1985, Int. J. Man Mach. Stud..

[149]  Brian Schott,et al.  Alternative Logics for Approximate Reasoning in Expert Systems: A Comparative Study , 1985, Int. J. Man Mach. Stud..

[150]  Pietro Torasso,et al.  Evidence Combination in Expert Systems , 1985, Int. J. Man Mach. Stud..

[151]  Alf C. Zimmer,et al.  What Uncertainty Judgments Can Tell About the Underlying Subjective Probabilities , 1985, UAI.

[152]  Tod S. Levitt.  Model-Based Probabilistic Situation Inference in Hierarchical Hypothesis Spaces , 1985, UAI.

[153]  David J. Spiegelhalter,et al.  Probabilistic Reasoning in Predictive Expert Systems , 1985, UAI.

[154]  Lotfi A. Zadeh,et al.  Is Probability Theory Sufficient for Dealing with Uncertainty in AI: A Negative View , 1985, UAI.

[155]  Ronald R. Yager,et al.  A General Approach to Decision Making with Evidential Knowledge , 1985, UAI.

[156]  Isaac Levi.  Decisions and Revisions - Philosophical Essays on Knowledge and Value , 1984 .

[157]  Harry E. Stephanou,et al.  A Set-Theoretic Framework for the Processing of Uncertain Knowledge , 1984, AAAI.

[158]  Thomas M. Strat.  Continuous Belief Functions for Evidential Reasoning , 1984, AAAI.

[159]  Robert E. Tarjan,et al.  Simple Linear-Time Algorithms to Test Chordality of Graphs, Test Acyclicity of Hypergraphs, and Selectively Reduce Acyclic Hypergraphs , 1984, SIAM J. Comput..

[160]  David Maier,et al.  Connections in Acyclic Hypergraphs , 1984, Theor. Comput. Sci..

[161]  Ronald R. Yager,et al.  Approximate reasoning as a basis for rule-based expert systems , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[162]  Casimir A. Kulikowski,et al.  A Practical Guide to Designing Expert Systems , 1984 .

[163]  T. Speed,et al.  Decomposable graphs and hypergraphs , 1984, Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics.

[164]  D. J. Spiegelhalter,et al.  Statistical and Knowledge‐Based Approaches to Clinical Decision‐Support Systems, with an Application in Gastroenterology , 1984 .

[165]  Claus-Rainer Rollinger.  Die Repräsentation natürlichsprachlich formulierten Wissens: Behandlung der Aspekte Unsicherheit und Satzverknüpfung , 1984 .

[166]  J. Ross Quinlan,et al.  Inferno: A Cautious Approach To Uncertain Inference , 1986, Comput. J..

[167]  N. Wermuth,et al.  Graphical and recursive models for contingency tables , 1983 .

[168]  K. Teigen.  Studies in subjective probability IV: probabilities, confidence, and luck , 1983 .

[169]  Elaine Rich,et al.  Default Reasoning as Likelihood Reasoning , 1983, AAAI.

[170]  Henri Prade,et al.  A Synthetic View of Approximate Reasoning Techniques , 1983, IJCAI.

[171]  Claus-Rainer Rollinger,et al.  How to Represent Evidence - Aspects of Uncertain Reasoning , 1983, IJCAI.

[172]  David Maier,et al.  The Theory of Relational Databases , 1983 .

[173]  R. Yager.  Some relationships between possibility, truth and certainty , 1983 .

[174]  S. Weber.  A general concept of fuzzy connectives, negations and implications based on t-norms and t-conorms , 1983 .

[175]  L. Zadeh.  The role of fuzzy logic in the management of uncertainty in expert systems , 1983 .

[176]  Judea Pearl,et al.  Reverend Bayes on Inference Engines: A Distributed Hierarchical Approach , 1982, AAAI.

[177]  M. Puri,et al.  A possibility measure is not a fuzzy measure , 1982 .

[178]  David Lindley.  Scoring rules and the inevitability of probability , 1982 .

[179]  Donald Michie,et al.  Introductory Readings in Expert Systems , 1982 .

[180]  John Douglas Lowrance,et al.  Dependency-graph models of evidential support , 1982 .

[181]  Drew McDermott,et al.  Nonmonotonic Logic II: Nonmonotonic Modal Theories , 1982, JACM.

[182]  Philippe Smets,et al.  The degree of belief in a fuzzy event , 1981, Inf. Sci..

[183]  P. Smets.  Medical diagnosis: Fuzzy sets and degrees of belief , 1981 .

[184]  Steven W. Zucker,et al.  On the Independence Assumption Underlying Subjective Bayesian Updating , 1981, Artif. Intell..

[185]  M. Yannakakis.  Computing the Minimum Fill-in is NP^Complete , 1981 .

[186]  Brian R. Gaines,et al.  Fuzzy reasoning and its applications , 1981 .

[187]  J. William,et al.  System aids in constructing consultation programs , 1981 .

[188]  Drew McDermott,et al.  Non-Monotonic Logic I , 1987, Artif. Intell..

[189]  Raymond Reiter,et al.  A Logic for Default Reasoning , 1987, Artif. Intell..

[190]  Peter Schefe.  On foundations of reasoning with uncertain facts and vague concepts , 1980 .

[191]  Masaharu Mizumoto,et al.  Several methods for fuzzy conditional inferences , 1979, 1979 18th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[192]  Casimir A. Kulikowski,et al.  EXPERT: A System for Developing Consultation Models , 1979, IJCAI.

[193]  Lotfi A. Zadeh,et al.  Approximate Reasoning Based on Fuzzy Logic , 1979, IJCAI.

[194]  Peter Szolovits,et al.  Categorical and Probabilistic Reasoning in Medical Diagnosis , 1990, Artif. Intell..

[195]  Casimir A. Kulikowski,et al.  A Model-Based Method for Computer-Aided Medical Decision-Making , 1978, Artif. Intell..

[196]  G. Schwarz.  Estimating the Dimension of a Model , 1978 .

[197]  V. Barnett,et al.  The Logical Foundations of Statistical Inference , 1977 .

[198]  D. Lewis.  Probabilities of Conditionals and Conditional Probabilities , 1976 .

[199]  E H Shorthffe,et al.  Computer-based medical consultations mycin , 1976 .

[200]  Edward H. Shortliffe,et al.  A model of inexact reasoning in medicine , 1990 .

[201]  G. Matheron.  Random Sets and Integral Geometry , 1976 .

[202]  菅野 道夫,et al.  Theory of fuzzy integrals and its applications , 1975 .

[203]  L. A. ZADEH,et al.  The concept of a linguistic variable and its application to approximate reasoning - I , 1975, Inf. Sci..

[204]  Lotfi A. Zadeh,et al.  Similarity relations and fuzzy orderings , 1971, Inf. Sci..

[205]  Patrick Suppes,et al.  Foundations of measurement , 1971 .

[206]  E. Torgersen.  Comparison of experiments when the parameter space is finite , 1970 .

[207]  M. Tribus.  Rational descriptions, decisions, and designs , 1969 .

[208]  P. Suppes.  Probabilistic Inference and the Concept of Total Evidence , 1969 .

[209]  L. Zadeh.  Probability measures of Fuzzy events , 1968 .

[210]  Cedric A. B. Smith,et al.  Personal Probability and Statistical Analysis , 1965 .

[211]  V. Strassen,et al.  Me\fehler und Information , 1964 .

[212]  N. N. Vorob’ev.  Consistent Families of Measures and Their Extensions , 1962 .

[213]  Howard Raiffa,et al.  Applied Statistical Decision Theory. , 1961 .

[214]  H. Kyburg.  Probability and Rationality , 1961 .

[215]  Cedric A. B. Smith,et al.  Consistency in Statistical Inference and Decision , 1961 .