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Adaptive Perspectives on Human–Technology InteractionMethods and Models for Cognitive Engineering and Human-Computer Interaction$
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Alex Kirlik

Print publication date: 2009

Print ISBN-13: 9780195374827

Published to Oxford Scholarship Online: March 2012

DOI: 10.1093/acprof:oso/9780195374827.001.0001

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Inferring Fast and Frugal Heuristics from Human Judgment Data

Inferring Fast and Frugal Heuristics from Human Judgment Data

Chapter:
(p.131) 10 Inferring Fast and Frugal Heuristics from Human Judgment Data
Source:
Adaptive Perspectives on Human–Technology Interaction
Author(s):

Ling Rothrock

Alex Kirlik

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195374827.003.0013

This chapter reports a formal technique developed to enable an analyst to infer heuristic judgment or strategies directly from behavioral data on human judgment. Although the technique is not yet fully mature, it provides at least one step toward the day when formal modeling of judgment and decision making in naturalistic or technological contexts may possibly become one useful item in the toolbox of a practitioner in cognitive engineering, human factors, and applied psychology. In addition, the technique that has been developed for inducing noncompensatory judgment policies from exemplars—genetics-based policy capturing (GBPC)—is described. Generally, GBPC holds promise for the design of advanced training technologies that use individual performance histories to target feedback toward eliminating any potential misconceptions or oversimplifications a trainee's behavior might reflect. It can also advance the science of judgment and decision making, at least in the realms of naturalistic decision making (NDM) and ecological rationality.

Keywords:   genetics-based policy capturing, human judgment, heuristic judgment, feedback, decision making, naturalistic decision making, ecological rationality

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