Decision fusion by people: Experiments, models, and sociotechnical system design

Aditya Vempaty, Lav R. Varshney, Gregory J. Koop, Amy H. Criss, Pramod K. Varshney

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

4 Scopus citations

Abstract

People and machines perform tasks differently. Building optimal systems that include people and machines, requires understanding their respective behavioral properties. The task of decision fusion is considered and the performance of people is compared to the optimal fusion rule. Our behavioral experiments demonstrate that people perform decision fusion in a stochastic manner dependent on various factors, whereas optimal rule is deterministic. A Bayesian hierarchical model is developed to characterize the observed human behavior. This model captures the differences observed in people at individual level, crowd level, and population level. The implications of such a model on developing large-scale human-machine systems are presented by developing optimal decision fusion trees with both human and machine agents.

Original languageEnglish (US)
Title of host publication2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages83-87
Number of pages5
ISBN (Electronic)9781479975914
DOIs
StatePublished - Feb 23 2016
EventIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 - Orlando, United States
Duration: Dec 13 2015Dec 16 2015

Publication series

Name2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

Other

OtherIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
CountryUnited States
CityOrlando
Period12/13/1512/16/15

Keywords

  • Bayesian hierarchical modeling
  • decision fusion
  • human decision-making
  • sociotechnical systems

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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