Reasoning Under Uncertainty: Variations of Subjective Logic Deduction

Abstract

This work develops alternatives to the classical subjective logic deduction operator. Given antecedent and consequent propositions, the new operators form opinions of the consequent that match the variance of the consequent posterior distribution given opinions on the antecedent and the conditional rules connecting the antecedent with the consequent. As a result, the uncertainty of the consequent actually map to the spread for the probability projection of the opinion. Monte Carlo simulations demonstrate this connection for the new operators. Finally, the work uses Monte Carlo simulations to evaluate the quality of fusing opinions from multiple agents before and after deduction.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2013
Accession Number
ADA615505

Entities

People

  • Chatschik Bisdikian
  • Geeth De Mel
  • Lance Kaplan
  • Murat Şensoy
  • Supriyo Chakraborty
  • Yuqing Tang

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Computational Science
  • Data Science
  • Estimators
  • Information Science
  • Military Research
  • Monte Carlo Method
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Reasoning
  • Simulations
  • Statistical Analysis
  • Statistics
  • Uncertainty

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  • Artificial Intelligence
  • Computational Modeling and Simulation