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 language | English (US) |
|---|---|
| Title of host publication | Adaptive Perspectives on Human-Technology Interaction |
| Subtitle of host publication | Methods and Models for Cognitive Engineering and Human-Computer Interaction |
| Publisher | Oxford University Press |
| ISBN (Electronic) | 9780199847693 |
| ISBN (Print) | 9780195374827 |
| DOIs | |
| State | Published - Mar 22 2012 |
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Keywords
- Decision making
- Ecological rationality
- Feedback
- Genetics-based policy capturing
- Heuristic judgment
- Human judgment
- Naturalistic decision making
ASJC Scopus subject areas
- Psychology(all)
Cite this
Inferring Fast and Frugal Heuristics from Human Judgment Data. / Rothrock, Ling; Kirlik, Alex.
Adaptive Perspectives on Human-Technology Interaction: Methods and Models for Cognitive Engineering and Human-Computer Interaction. Oxford University Press, 2012.Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Inferring Fast and Frugal Heuristics from Human Judgment Data
AU - Rothrock, Ling
AU - Kirlik, Alex
PY - 2012/3/22
Y1 - 2012/3/22
N2 - 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.
AB - 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.
KW - Decision making
KW - Ecological rationality
KW - Feedback
KW - Genetics-based policy capturing
KW - Heuristic judgment
KW - Human judgment
KW - Naturalistic decision making
UR - http://www.scopus.com/inward/record.url?scp=84920643454&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84920643454&partnerID=8YFLogxK
U2 - 10.1093/acprof:oso/9780195374827.003.0013
DO - 10.1093/acprof:oso/9780195374827.003.0013
M3 - Chapter
AN - SCOPUS:84920643454
SN - 9780195374827
BT - Adaptive Perspectives on Human-Technology Interaction
PB - Oxford University Press
ER -