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Publication Detail
A cognitively bounded rational analysis model of dual-task performance trade-offs
  • Publication Type:
    Journal article
  • Authors:
    Janssen CP, Brumby DP, Dowell J, Chater N
  • Publisher:
    Drexel University
  • Publication date:
  • Place of publication:
    Philadelphia, PA
  • Pagination:
    103, 108
  • Journal:
    Proceedings of the 10th international conference on cognitive modeling
  • Editors:
    Salvucci DD,Gunzelmann G
  • Status:
  • Language:
  • Keywords:
    Multitasking, Performance Operating Characteristics, Cognitively Bounded Rational Analysis
  • Notes:
    Winner of Allen Newell prize for best student paper. A more elaborate version of this has been accepted as a journal paper for Topics in Cognitive Science. The title of that paper is: "Identifying Optimum Performance Trade-Offs using a Cognitively Bounded Rational Analysis Model of Discretionary Task Interleaving"
The process of interleaving two tasks can be described as making trade-offs between performance on each of the tasks.This can be captured in performance operating characteristic curves. However, these curves do not describe what, given the specific task circumstances, the optimal strategy is. In this paper we describe the results of a dual-task study in which participants performed a tracking and typing task under various experimental conditions. An objective payoff function was used to describe how participants should trade-off performance between the tasks. Results show that participants’ dual-task interleaving strategy was sensitive to changes in the difficulty of the tracking task, and resulted in differences in overall task performance. To explain the observed behavior, a cognitively bounded rational analysis model was developed to understand participants’ strategy selection. This analysis evaluated a variety of dual-task interleaving strategies against the same payoff function that participants were exposed to. The model demonstrated that in three out of four conditions human performance was optimal; that is, participants adopted dual-task strategies that maximized the payoff that was achieved.
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