Uncertainty, belief, and probability 1

We introduce a new probabilistic approach to dealing with uncertainty, based on the observation that probability theory does not require that every event be assigned a probability. For a nonmeasurable event (one to which we do not assign a probability), we can talk about only the inner measure and outer measure of the event. In addition to removing the requirement that every event be assigned a probability, our approach circumvents other criticisms of probability‐based approaches to uncertainty. For example, the measure of belief in an event turns out to be represented by an interval (defined by the inner and outer measures), rather than by a single number. Further, this approach allows us to assign a belief (inner measure) to an event E without committing to a belief about its negation ‐E (since the inner measure of an event plus the inner measure of its negation is not necessarily one). Interestingly enough, inner measures induced by probability measures turn out to correspond in a precise sense to Dempster‐Shafer belief functions. Hence, in addition to providing promising new conceptual tools for dealing with uncertainty, our approach shows that a key part of the important Dempster‐Shafer theory of evidence is firmly rooted in classical probability theory.

[1]  Robert S. Boyer,et al.  The Correctness Problem in Computer Science , 1982 .

[2]  Joseph Y. Halpern,et al.  A Guide to the Modal Logics of Knowledge and Belief: Preliminary Draft , 1985, IJCAI.

[3]  John H. Reif,et al.  The complexity of elementary algebra and geometry , 1984, STOC '84.

[4]  Paul K. Black Is shafer general bayes? , 1988, Int. J. Approx. Reason..

[5]  A. Tarski A Decision Method for Elementary Algebra and Geometry , 2023 .

[6]  J. Kyburg Higher order probability and intervals , 1988 .

[7]  B. O. Koopman The Axioms and Algebra of Intuitive Probability , 1940 .

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

[9]  Paul R. Cohen,et al.  Heuristic reasoning about uncertainty: an artificial intelligence approach , 1984 .

[10]  Henry E. Kyburg,et al.  Bayesian and Non-Bayesian Evidential Updating , 1987, Artificial Intelligence.

[11]  Hans-Jürgen Zimmermann Fuzzy Logic and Approximate Reasoning , 1985 .

[12]  G. Choquet Theory of capacities , 1954 .

[13]  Nils J. Nilsson,et al.  Probabilistic Logic * , 2022 .

[14]  Feller William,et al.  An Introduction To Probability Theory And Its Applications , 1950 .

[15]  B. O. Koopman The bases of probability , 1940 .

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

[17]  Sandy L. Zabell,et al.  Some Alternatives to Bayes' Rule. , 1983 .

[18]  Henry E. Kyburg,et al.  Higher order probabilities and intervals , 1988, Int. J. Approx. Reason..

[19]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems , 1988 .

[20]  Hans Hermes,et al.  Introduction to mathematical logic , 1973, Universitext.

[21]  R. T. Cox Probability, frequency and reasonable expectation , 1990 .

[22]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[23]  Peter C. Cheeseman,et al.  In Defense of Probability , 1985, IJCAI.

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

[25]  Daniel Hunter,et al.  Dempster-Shafer vs. Probabilistic Logic , 1987, UAI 1987.

[26]  H. Jeffreys Logical Foundations of Probability , 1952, Nature.

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

[28]  Ronald Fagin,et al.  Two Views of Belief: Belief as Generalized Probability and Belief as Evidence , 1992, Artif. Intell..

[29]  Ronald Fagin,et al.  A new approach to updating beliefs , 1990, UAI.

[30]  Joseph Y. Halpern,et al.  A logic to reason about likelihood , 1983, Artif. Intell..

[31]  John F. Canny,et al.  Some algebraic and geometric computations in PSPACE , 1988, STOC '88.

[32]  Henry E. Kyburg,et al.  Probability and the logic of rational belief , 1970 .

[33]  John F. Lemmer,et al.  Confidence Factors, Empiricism and the Dempster-Shafer Theory of Evidence , 1985, UAI.

[34]  Irving John Good,et al.  Subjective Probability as the Measure of a Non-measurable Set , 1962 .

[35]  Ronald Fagin,et al.  A logic for reasoning about probabilities , 1988, [1988] Proceedings. Third Annual Information Symposium on Logic in Computer Science.

[36]  Leslie Pack Kaelbling,et al.  The Synthesis of Digital Machines With Provable Epistemic Properties , 1986, TARK.

[37]  E. Rowland Theory of Games and Economic Behavior , 1946, Nature.

[38]  Lotfi A. Zadeh,et al.  Review of A Mathematical Theory of Evidence , 1984 .

[39]  T. Fine,et al.  Towards a Frequentist Theory of Upper and Lower Probability , 1982 .