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PROBabilities from EXemplars (PROBEX): a "lazy" algorithm for probabilistic inference from generic knowledge
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Psychology.
2002 (English)In: Cognitive science, ISSN 0364-0213, E-ISSN 1551-6709, Vol. 26, no 5, 563-607 p.Article in journal (Refereed) Published
Abstract [en]

PROBEX (PROBabilities from EXemplars), a model of probabilistic inference and probability judgmentbased on generic knowledge is presented. Its properties are that: (a) it provides an exemplar modelsatisfying bounded rationality; (b) it is a “lazy” algorithm that presumes no pre-computed abstractions;(c) it implements a hybrid-representation, similarity-graded probability. We investigate the ecologicalrationality of PROBEX and find that it compares favorably with Take-The-Best and multiple regression(Gigerenzer, Todd, & the ABC Research Group, 1999). PROBEX is fitted to the point estimates,decisions, and probability assessments by human participants. The best fit is obtained for a version thatweights frequency heavily and retrieves only two exemplars. It is proposed that PROBEX implementsspeed and frugality in a psychologically plausible way.

Place, publisher, year, edition, pages
2002. Vol. 26, no 5, 563-607 p.
Keyword [en]
PROBEX, Lazy algorithm, Probabilistic inference
National Category
Psychology
Identifiers
URN: urn:nbn:se:uu:diva-90824DOI: 10.1207/s15516709cog2605_2OAI: oai:DiVA.org:uu-90824DiVA: diva2:163307
Available from: 2003-09-11 Created: 2003-09-11 Last updated: 2013-06-10Bibliographically approved
In thesis
1. Bounded Rationality and Exemplar Models
Open this publication in new window or tab >>Bounded Rationality and Exemplar Models
2003 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Bounded rationality is the study of how human cognition with limited capacity is adapted to handle the complex information structures in the environment. This thesis argues that in order to understand the bounded rationality of decision processes, it is necessary to develop decision theories that are computational process models based upon basic cognitive and perceptual mechanisms. The main goal of this thesis is to show that models of perceptual categorization based on the storage of exemplars and retrieval of similar exemplars whenever a new object is encountered (D. L. Medin & M. M. Schaffer, 1978), can be an important contribution to theories of decision making. Study I proposed, PROBEX (PROBabilities from Exemplars), a model for inferences from generic knowledge. It is a “lazy” algorithm that presumes no pre-computed abstractions. In a computer simulation it was found to be a powerful decision strategy, and it was possible to fit the model to human data in a psychologically plausible way. Study II was a theoretical investigation that found that PROBEX was very robust in conditions where the decision maker has very little information, and that it worked well even under the worst circumstances. Study III empirically tested if humans can learn to use exemplar based or one reason decision making strategies (G. Gigerenzer, P. Todd, & the ABC Research Group, 1999) where it is appropriate in a two-alternative choice task. Experiment 1 used cue structure and presentation format as independent variables, and participants easily used one reason strategies if the decision task presented the information as normal text. The participants were only able to use exemplars if they were presented as short strings of letters. Experiment 2 failed to accelerate learning of exemplar use during the decision phase, by prior exposure to exemplars in a similar task. In conclusion, this thesis supports that there are at least two modes of decision making, which are boundedly rational if they are used in the appropriate context. Exemplar strategies may, contrary to study II, only be used late in learning, and the conditions for learning need to be investigated further.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2003. 48 p.
Series
Comprehensive Summaries of Uppsala Dissertations from the Faculty of Social Sciences, ISSN 0282-7492 ; 131
Keyword
Psychology, PROBEX, Lazy Algorithm, Probabilistic Inference, Decision Making, Bounded Rationality, Ecological Rationality, Take The Best, exemplar models, correspondence, Psykologi
National Category
Psychology
Research subject
Psychology
Identifiers
urn:nbn:se:uu:diva-3572 (URN)91-554-5733-9 (ISBN)
Public defence
2003-10-02, Lärosal IV, Universitetshuset, Uppsala, 13:15
Opponent
Supervisors
Available from: 2003-09-11 Created: 2003-09-11Bibliographically approved

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