Representing the task in Bayesian reasoning: Comment on Lovett and Schunn (1999) (2000)
Authors
Abstract
The RCCL model (M. C. Lovett and C. D. Schunn, 1999; see record 1999-05245-001) produces predictions that are non-novel or that do not truly spring from its principles. However, it offers the valuable insight that learning processes may affect the selection of both representations and strategies within those representations, and points the way to possible theoretical progress on implicit and explicit control. The authors' account of base-rate neglect under direct experience is compared with RCCL, and it is concluded that learning-based models allow for tests that are not fostered by representation-based models. (PsycINFO Database Record (c) 2012 APA, all rights reserved) (journal abstract)
Bibliographic entry
Goodie, A. S., & Fantino, E. (2000). Representing the task in Bayesian reasoning: Comment on Lovett and Schunn (1999). Journal of Experimental Psychology: General, 129, 449-452.
Miscellaneous
| Publication year | 2000 | |
|---|---|---|
| Document type: | Article | |
| Publication status: | Published | |
| External URL: | ||
| Categories: | Forecasting | |
| Keywords: | *choice behavior*cognitive processes*information*response variabilitycognitive hypothesis testingcuesmodels |