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The bounds of cognitive heuristic performance on the geographic profiling task
Author(s) -
Taylor Paul J.,
Bennell Craig,
Snook Brent
Publication year - 2009
Publication title -
applied cognitive psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 100
eISSN - 1099-0720
pISSN - 0888-4080
DOI - 10.1002/acp.1469
Subject(s) - heuristics , profiling (computer programming) , prioritization , heuristic , psychology , task (project management) , cognition , cognitive load , computer science , machine learning , cognitive psychology , artificial intelligence , management science , engineering , systems engineering , neuroscience , operating system
Human performance on the geographic profiling task—where the goal is to predict an offender's home location from their crime locations—has been shown to equal that of complex actuarial methods when it is based on appropriate heuristics. However, this evidence is derived from comparisons of ‘X‐marks‐the‐spot’ predictions, which ignore the fact that some algorithms provide a prioritization of the offender's area of spatial activity. Using search area as a measure of performance, we examine the predictions of students ( N = 200) and an actuarial method under three levels of information load and two levels of heuristic‐environment fit. Results show that the actuarial method produces a smaller search area than a concentric search outward from students' ‘X‐marks‐the‐spot’ predictions, but that students are able to produce search areas that are smaller than those provided by the actuarial method. Students' performance did not decrease under greater information load and was not improved by adding a descriptive qualifier to the taught heuristic. Copyright © 2008 John Wiley & Sons, Ltd.