PRIOR PROBABILITY, TWO-PERSON GAMES AND INFORMATION THEORY,

Abstract

The prior probability of a certain variable B is determined using all the available deterministic knowledge such as (1) the variable B may not be observable, but only a related variable Z may be observable so that P(Z/B) is known; (2) the probability distributions that can be assumed by B are limited by the inequalities E(h sub k (B)) > or = o where h sub k (B) are known functions. The prior probability is determined by a two-person zero-sum game which deals with the gambling on the outcomes of the observable variable Z. The prior probability distribution determined in this manner is the same as that obtained by maximizing the average uncertainty associated with the variable B given that variable Z is observable. An expression will be obtained for the uncertainty function starting with a set of axioms and the expression is the same as the Shannon mutual information I(B;Z) between the variables B and Z. (Author)

Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1969
Accession Number
AD0698773

Entities

People

  • R. L. Kashyap

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Ergodic Processes
  • Gambling
  • Inequalities
  • Information Theory
  • Mathematics
  • Probability
  • Probability Distributions
  • Stochastic Processes
  • Uncertainty
  • Zero-Sum Games

Readers

  • Game Theory.
  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.