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Team situation awareness measure using semantic utility functions for supporting dynamic decision-making

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Abstract

Team decision-making is a remarkable feature in a complex dynamic decision environment, which can be supported by team situation awareness. In this paper, a team situation awareness measure (TSAM) method using a semantic utility function is proposed. The semantic utility function is used to clarify the semantics of qualitative information expressed in linguistic terms. The individual and team situation awareness are treated as linguistic possibility distributions on the potential decisions in a dynamic decision environment. In the TSAM method, team situation awareness is generated through reasoning and aggregating individual situation awareness based on a multi-level hierarchy mental model of the team. Individual and team mental models are composed of key drivers and significant variables. An illustrative example in telecoms customer churn prediction is given to explain the effectiveness and the main steps of the TSAM method.

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Acknowledgments

The work presented in this paper was supported by Australian Research Council (ARC) under Discovery Project DP0559213 and DP0880739. The authors sincerely appreciate the advice and suggestions of Professor Da Ruan from the Belgian Nuclear Research Center (SCK CEN).

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Authors and Affiliations

  1. Centre of QCIS, Faculty of Engineering and Information Technology, University of Technology, Sydney (UTS), PO Box 123, Broadway, Sydney, NSW, 2007, Australia

    Jun Ma, Jie Lu & Guangquan Zhang

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  1. Jun Ma
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  2. Jie Lu
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  3. Guangquan Zhang
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Correspondence to Jun Ma.

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Ma, J., Lu, J. & Zhang, G. Team situation awareness measure using semantic utility functions for supporting dynamic decision-making. Soft Comput 14, 1305–1316 (2010). https://doi.org/10.1007/s00500-009-0500-7

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