Inferring Fast and Frugal Heuristics from Human Judgment Data

Ling Rothrock, Alex Kirlik

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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.

Original languageEnglish (US)
Title of host publicationAdaptive Perspectives on Human-Technology Interaction
Subtitle of host publicationMethods and Models for Cognitive Engineering and Human-Computer Interaction
PublisherOxford University Press
ISBN (Electronic)9780199847693
ISBN (Print)9780195374827
DOIs
StatePublished - Mar 22 2012

All Science Journal Classification (ASJC) codes

  • Psychology(all)

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    Rothrock, L., & Kirlik, A. (2012). Inferring Fast and Frugal Heuristics from Human Judgment Data. In Adaptive Perspectives on Human-Technology Interaction: Methods and Models for Cognitive Engineering and Human-Computer Interaction Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195374827.003.0013