Collaborative human decision fusion with uncertain individual thresholds

Thakshila Wimalajeewa, Pramod K. Varshney

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

2 Scopus citations

Abstract

In this paper, we propose a collaborative decision fusion framework when the participants of the decision making process are human agents. We consider a binary hypothesis testing problem in which a group of n people makes individual decisions on which hypothesis is true based on their own knowledge and perception. The observations at individual agents are assumed to be corrupted by a common as well as independent noise signals. Local decisions made at individual agents are sent to a moderator (fusion center) to make the final decision. We assume that the moderator has imperfect knowledge about the thresholds used by the individual decision makers and model them as random variables. The fusion performance in terms of the probability of error at the moderator is derived when the exact realizations of the individual thresholds of the agents are not available. With two human agents in the group, we derive the performance of the likelihood ratio based decision fusion strategy. For an arbitrary number of human agents n(> 2), we derive performance of decision fusion with majority rule using certain approximations.

Original languageEnglish (US)
Title of host publication15th International Conference on Information Fusion, FUSION 2012
Pages1210-1217
Number of pages8
StatePublished - Oct 24 2012
Event15th International Conference on Information Fusion, FUSION 2012 - Singapore, Singapore
Duration: Sep 7 2012Sep 12 2012

Publication series

Name15th International Conference on Information Fusion, FUSION 2012

Other

Other15th International Conference on Information Fusion, FUSION 2012
CountrySingapore
CitySingapore
Period9/7/129/12/12

ASJC Scopus subject areas

  • Information Systems

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  • Cite this

    Wimalajeewa, T., & Varshney, P. K. (2012). Collaborative human decision fusion with uncertain individual thresholds. In 15th International Conference on Information Fusion, FUSION 2012 (pp. 1210-1217). [6289946] (15th International Conference on Information Fusion, FUSION 2012).