Anticipated variability increases generalization of predictive learning.

ABSTRACT: We show that learners generalized more broadly around the learned stimulus when they expected more variability between the learning set and the generalization set, as well as within the generalization set. Experiments 1 and 3 used a predictive learning task and demonstrated border perceptual generalization both when expected variability was manipulated explicitly via instructions (Experiment 1), and implicitly by increasing temporal distance to the anticipated application of learning (Experiment 3). Experiment 2 showed that expecting to apply learning in the more distant future increases expected variability in the generalization set. We explain the relation between expected variability and generalization as an accuracy-applicability trade-off: when learners anticipate more variable genera

SUBMITTER: Ram H 

PROVIDER: S-EPMC11380665 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature