A STUDY IN PROBABILISTIC INFORMATION PROCESSING (PIP)

Abstract

Men required to choose among alternative hypotheses given fallible data fail to extract as much "certainty" as the data justify. PIP Theory indicates that performance can be improved by using Bayesian probability judgements. This experiment was designed to test this theory. Subjects, receiving simulated military data, determinined which one of three strategies (Hypotheses) an enemy was using. In the NON-PIP condition subjects estimated P(H/D) directly. In the PIP condition subjects estimated P(D/H), and P(H/D) was calculated using Bayes Formula. Results show: (1) the highest probability was always assigned to the correct hypothesis. (2) PIP was superior to NON-PIP in (a) achieving higher posterior probabilities, and (b) reaching asymptotes faster. (3) Increasing difficulty resulted in poorer performance in NON-PIP.

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Document Details

Document Type
Technical Report
Publication Date
Apr 02, 1963
Accession Number
AD0402145

Entities

People

  • J. R. Newman
  • Richard J. Kaplan

Organizations

  • System Development Corporation

Tags

Communities of Interest

  • Counter IED
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • California
  • Computer Programs
  • Computers
  • Data Analysis
  • Databases
  • Experimental Design
  • Information Processing
  • Information Science
  • Information Systems
  • Instructions
  • Judgment
  • Materials
  • Monte Carlo Method
  • Pilot Studies
  • Probability
  • United States

Readers

  • Materials Science.
  • Statistical inference.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference