Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/58416
Type: | Conference paper |
Title: | Confirmation bias is rational when hypotheses are sparse |
Author: | Perfors, A. Navarro, D. |
Citation: | Proceedings of the 31st Annual Conference of the Cognitive Science Society (COGSCI 2009): pp.2741-2746 |
Publisher: | Cognitive Science Society |
Publisher Place: | Netherlands |
Issue Date: | 2009 |
ISBN: | 9780976831853 |
Conference Name: | Annual Conference of the Cognitive Science Society (31st : 2009 : Amsterdam, The Netherlands) |
Statement of Responsibility: | Amy Perfors and Daniel Navarro |
Abstract: | We consider the common situation in which a reasoner must induce the rule that explains an observed sequence of data, but the hypothesis space of possible rules is not explicitly enumerated or identified; an example of this situation is the number game (Wason, 1960), or "twenty questions." We present mathematical optimality results showing that as long as hypotheses are sparse -- that is, as long as rules, on average, tend to be true only for a small proportion of entities in the world -- then confirmation bias is a near-optimal strategy. Experimental evidence suggests that at least in the domain of numbers, the sparsity assumption is reasonable. |
Keywords: | rational analysis decision making confirmation bias information |
Rights: | © the authors |
Appears in Collections: | Aurora harvest 5 Psychology publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
hdl_58416.pdf | Published version | 99.65 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.