People apply what they learn from experience not only to the experienced stimuli, but also to novel stimuli. But what determines how widely people generalize what they have learned? Using a predictive learning paradigm, we examined the hypothesis that a low (vs. high) probability of an outcome following a predicting stimulus would widen generalization. In three experiments, participants learned which stimulus predicted an outcome (S+) and which stimulus did not (S-) and then indicated how much they expected the outcome after each of eight novel stimuli ranging in perceptual similarity to S+ and S-. The stimuli were rings of different sizes and the outcome was a picture of a lightning bolt. As hypothesized, a lower probability of the outcome widened generalization. That is, novel stimuli that were similar to S+ (but not to S-) produced expectations for the outcome that were as high as those associated with S+.
|Number of pages||17|
|State||Published - 2019|
Bibliographical noteFunding Information:
This work was supported by the I-CORE Program of the Planning and Budgeting Committee and the Israel Science Foundation (Grant 51/11) and by a Center for Excellence grant from the University of Leuven – KU Leuven (PF/10/005).
© 2019 Hogrefe Publishing.
- learning from experience
- partial reinforcement
- predictive learning