INFORMATION AMOUNT AS A MEASURE CORRECTING ONE'S PRIOR PROBABILITY.

Abstract

Several kinds of definition of information amount or information value have been proposed by several authors. The author attempts to define information amount as a measure of correcting one's prior probability distribution on the state space. By combining two informations concerning the same decision partition, it is shown that the combined information has a greater information amount than the separate ones. When two different types of informations - in the sense they are concerned with different decision sub-partitions of the ultimate decision partition - it is shown how they should be aggregated to obtain a more informative information concerning the ultimate decision partition. (Author)

Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1965
Accession Number
AD0617326

Entities

People

  • Koichi Miyasawa

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Mathematics
  • Probability
  • Probability Distributions

Readers

  • Graph Algorithms and Convex Optimization.
  • Systems Analysis and Design
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • Space