Heuristic Classification in a Simulated Air Threat Task

Classification Heuristique dans le Cadre d’une Simulation de Tâche Liée aux Menaces Aériennes


  1. Bryant, D.J.
Corporate Authors
Defence R&D Canada - Toronto, Toronto ONT (CAN)
Fast and frugal heuristics have proved effective models of human judgment for certain kinds of problems. To further explore the value of this approach, two experiments investigated the decision procedures used by human subjects to perform a cue-based classification task in a simulated air threat assessment task. Threat assessment is the classification of aircraft on the basis of sensor data that can be likened to probabilistic cues. Subjects learned to classify simulated aircraft using four probabilistic cues then classified test sets designed to contrast predictions of several heuristics, including the Take-the-Best-for-Classification (TTB-C) and Pros Rule developed specifically for the threat classification task. Results indicated that a proportion of subjects could be classified using TTB-C and another significant proportion as using the less frugal Pros Rule. No subject was observed to respond as predicted by a Bayesian strategy. Despite predictions that time pressure and perceived uncertainty of cues would affect how many subjects employed TTB-C, no effect of these variables was observed. These results suggest that it is possible to model multi-attribute decision tasks like threat assessment with fast and frugal heuristics but no single heuristic is a general model for the simulated threat assessment task.

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heuristics;threat assessment;probabilistic cues
Report Number
DRDC-TORONTO-TR-2005-191 — Technical Report
Date of publication
16 Jun 2005
Number of Pages
Electronic Document(PDF)

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