A new understanding of subjective probability and its generalization to lower and upper prevision

Abstract This article introduces a new way of understanding subjective probability and its generalization to lower and upper prevision. Instead of asking whether a person is willing to pay given prices for given risky payoffs, we ask whether the person believes he can make a lot of money at those prices. If not––if the person is convinced that no strategy for exploiting the prices can make him very rich in the long run––then the prices measure his subjective uncertainty about the events involved. This new understanding justifies Peter Walley’s updating principle, which applies when new information is anticipated exactly. It also justifies a weaker principle that is more useful for planning because it applies even when new information is not anticipated exactly. This weaker principle can serve as a basis for flexible probabilistic planning in event trees.

[1]  Arie Tzvieli Possibility theory: An approach to computerized processing of uncertainty , 1990, J. Am. Soc. Inf. Sci..

[2]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1967 .

[3]  R. Durrett Probability: Theory and Examples , 1993 .

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

[5]  Christian P. Robert,et al.  The Bayesian choice , 1994 .

[6]  J. Doob Stochastic processes , 1953 .

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

[8]  L. Wasserman,et al.  Inferences from multinomial data: Learning about a bag of marbles - Discussion , 1996 .

[9]  P G rdenfors,et al.  Knowledge in flux: modeling the dynamics of epistemic states , 1988 .

[10]  H. Teicher,et al.  Probability theory: Independence, interchangeability, martingales , 1978 .

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

[12]  B. D. Finetti La prévision : ses lois logiques, ses sources subjectives , 1937 .

[13]  Romano Scozzafava,et al.  Characterization of coherent Conditional Probabilities as a Tool for their Assessment and Extension , 1996, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[14]  Mark Bickford,et al.  A Logic of Events , 2003 .

[15]  P. Walley Inferences from Multinomial Data: Learning About a Bag of Marbles , 1996 .

[16]  Hirofumi Katsuno,et al.  On the Difference between Updating a Knowledge Base and Revising It , 1991, KR.

[17]  G. Shafer Causality and Responsibility , 2002 .

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

[19]  A. P. Dawid,et al.  Present position and potential developments: some personal views , 1984 .

[20]  William Feller,et al.  An Introduction to Probability Theory and Its Applications , 1951 .

[21]  G. Shafer Bayes's Two Arguments for The Rule of Conditioning , 1982 .

[22]  I. Levi On Indeterminate Probabilities , 1974 .

[23]  Glenn Shafer,et al.  Mathematical foundations for probability and causality , 1998 .

[24]  Peter Walley,et al.  Towards a unified theory of imprecise probability , 2000, Int. J. Approx. Reason..

[25]  R. P. Srivastava,et al.  Belief functions in business decisions , 2002 .

[26]  Klemens Szaniawski,et al.  Formal methods in the methodology of empirical sciences : proceedings of the Conference for Formal Methods in the Methodology of Empirical Sciences, Warsaw, June 17-21, 1974 , 1976 .

[27]  P. Walley Statistical Reasoning with Imprecise Probabilities , 1990 .

[28]  G. Shafer,et al.  Probability and Finance: It's Only a Game! , 2001 .

[29]  Henry E. Kyburg,et al.  Studies in Subjective Probability , 1965 .

[30]  Isaac Levi,et al.  The Enterprise Of Knowledge , 1980 .

[31]  Glenn Shafer,et al.  The art of causal conjecture , 1996 .