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Abstract

Human performance modeling approaches (HPMAs) that are comprehensive and computational are particularly useful for system development. Current comprehensive approaches have strengths in modeling a person's actions, but lack mathematical foundations that inherently yield information about the time and capacity related performance of the human in the system. This paper proposes a complementary approach called the Queuing Network Model Human Processor (QNMHP) that combines elements of the GOMS/Model Human Processor approach with the mathematical concept of queuing networks. A general queuing network representing the human and methodology for using this network are discussed in light of current efforts to model a steering task.

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The Queuing Network Model Human Processor (QNMHP): An Engineering Approach for Modeling Cognitive Performance

Abstract

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