Simulating human decision making for testing soft and hard/soft fusion algorithms

Donald J. Bucci, Sayandeep Acharya, Moshe Kam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Current methods for evaluating the effects of human opinions in data fusion systems are often dependent on human testing (which is logistically hard and difficult to arrange for repeated tests of the same population). The alternative is to use hypothetical examples, which tend to be simplistic. To facilitate studies of data fusion architectures which integrate ¿soft¿ human-generated decisions, we have used a simulator of subjective beliefs. The simulator is based on the two-stage dynamic signal detection model of Pleskac and Busemeyer (2010). We use this scheme to simulate human opinions and combine them using belief fusion methods, including Bayes' Rule; Dempster's Rule of Combination (DRC); Yager's rule; the Proportional Conflict Redistribution Rule #5 (PCR5) from Dezert-Smarandache theory; and the consensus operator from subjective logic. In our simulations, the DRC and Bayes rule exhibited performance that was on par with, and in some cases better than PCR5 and the consensus operator (when used in conjunction with a measure of source reliability). In all simulated cases, Yager's rule exhibited inferior performance.

Original languageEnglish (US)
Title of host publication2013 47th Annual Conference on Information Sciences and Systems, CISS 2013
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 47th Annual Conference on Information Sciences and Systems, CISS 2013 - Baltimore, MD, United States
Duration: Mar 20 2013Mar 22 2013

Publication series

Name2013 47th Annual Conference on Information Sciences and Systems, CISS 2013

Other

Other2013 47th Annual Conference on Information Sciences and Systems, CISS 2013
CountryUnited States
CityBaltimore, MD
Period3/20/133/22/13

All Science Journal Classification (ASJC) codes

  • Information Systems

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