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- W967843546 abstract "Human judgment in a wide array of areas can be captured, measured, analyzed, and facilitated. Human judgment in a given domain is shaped by the feedback received over time concerning how judgments compare to the standards of accuracy in that domain. The information received may be in the form of cognitive feedback. In that case, the judgmental policy will be analyzed and compared to the known optimal judgmental model. More often, though, outcome feedback is obtained, that is, information only about how accurate each of one's judgments turned out to be. Using outcome feedback to learn is described as “the hard way,” as it makes learning difficult even in a deterministic environment. The outcomes observed are prone to inscrutable variation due to unknown controlling variables, inaccurate feedback, and perhaps even some truly random error. The basic Brunswikian view of learning gives rise to a paradigm for laboratory studies of learning in probabilistic environments, usually referred to as multiple cue probability learning (MCPL). The MCPL paradigm captures several important features of learning from feedback in natural situations." @default.
- W967843546 created "2016-06-24" @default.
- W967843546 creator A5046096468 @default.
- W967843546 date "1988-01-01" @default.
- W967843546 modified "2023-10-13" @default.
- W967843546 title "Chapter 4 On the How and Why (not) of Learning from Outcomes" @default.
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- W967843546 doi "https://doi.org/10.1016/s0166-4115(08)62172-x" @default.
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