Experience matters: Information acquisition optimizes probability gain (2010)
Abstract
Deciding which piece of information to acquire or attend to is fundamental to perception, categorization, medical diagnosis, and scientific inference. Four statistical theories of the value of information-information gain, Kullback-Liebler distance, probability gain (error minimization), and impact-are equally consistent with extant data on human information acquisition. Three experiments, designed via computer optimization to be maximally informative, tested which of these theories best describes human information search. Experiment 1, which used natural sampling and experience-based learning to convey environmental probabilities, found that probability gain explained subjects' information search better than the other statistical theories or the probability-of-certainty heuristic. Experiments 1 and 2 found that subjects behaved differently when the standard method of verbally presented summary statistics (rather than experience-based learning) was used to convey environmental probabilities. Experiment 3 found that subjects' preference for probability gain is robust, suggesting that the other models contribute little to subjects' search behavior.
Bibliographic entry
Nelson, J. D., McKenzie, C. R. M., Cottrell, G. W., & Sejnowski, T. J. (2010). Experience matters: Information acquisition optimizes probability gain. Psychological Science, 21, 960-969. doi:10.1177/0956797610372637 (Full text)
Miscellaneous
| Publication year | 2010 | |
|---|---|---|
| Document type: | Article | |
| Publication status: | Published | |
| External URL: | http://dx.doi.org/10.1177/0956797610372637 View | |
| Categories: | HealthProbability | |
| Keywords: | humanslearninglearning: physiologyprobabilitypsychological theorystudentsstudents: psychologytask performance and analysis |