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Literature DB >> 28121026

Probability Learning: Changes in Behavior Across Time and Development.

Rista C Plate¹, Jacqueline M Fulvio¹, Kristin Shutts¹, C Shawn Green¹, Seth D Pollak¹.

Abstract

Individuals track probabilities, such as associations between events in their environments, but less is known about the degree to which experience-within a learning session and over development-influences people's use of incoming probabilistic information to guide behavior in real time. In two experiments, children (4-11 years) and adults searched for rewards hidden in locations with predetermined probabilities. In Experiment 1, children (n = 42) and adults (n = 32) changed strategies to maximize reward receipt over time. However, adults demonstrated greater strategy change efficiency. Making the predetermined probabilities more difficult to learn (Experiment 2) delayed effective strategy change for children (n = 39) and adults (n = 33). Taken together, these data characterize how children and adults alike react flexibly and change behavior according to incoming information.

Entities: Chemical Disease Gene Species

Mesh：

Year: 2017 PMID： 28121026 PMCID： PMC5526727 DOI： 10.1111/cdev.12718

Source DB: PubMed Journal: Child Dev ISSN： 0009-3920

13 in total

1. Supplementary report: the utility of correctly predicting infrequent events.

Authors: Y BRACKBILL; A BRAVOS
Journal: J Exp Psychol Date: 1962-12

2. A further test of a general utility theory model for probability learning.

Authors: K B LITTLE; Y BRACKBILL; R B ISAACS; N SMELKINSON
Journal: J Exp Psychol Date: 1963-07

3. When children are better (or at least more open-minded) learners than adults: developmental differences in learning the forms of causal relationships.

Authors: Christopher G Lucas; Sophie Bridgers; Thomas L Griffiths; Alison Gopnik
Journal: Cognition Date: 2014-02-22

Probability Learning: Changes in Behavior Across Time and Development.

1. Supplementary report: the utility of correctly predicting infrequent events.

2. A further test of a general utility theory model for probability learning.

3. When children are better (or at least more open-minded) learners than adults: developmental differences in learning the forms of causal relationships.

4. Rational variability in children's causal inferences: the Sampling Hypothesis.

5. Children use categories to maximize accuracy in estimation.

6. Causal learning from probabilistic events in 24-month-olds: an action measure.

7. Alterations in choice behavior by manipulations of world model.

8. Win-Stay, Lose-Sample: a simple sequential algorithm for approximating Bayesian inference.

9. Intuitive statistics by 8-month-old infants.

Review 10. Reconstructing constructivism: causal models, Bayesian learning mechanisms, and the theory theory.

Review 1. Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements.

2. Testimony bias lingers across development under uncertainty.

3. Attentional mechanisms drive systematic exploration in young children.

4. Balancing exploration and exploitation with information and randomization.

Review 5. Reinforcement learning across development: What insights can we draw from a decade of research?

6. Children's value-based decision making.

7. Probability matching is not the default decision making strategy in human and non-human primates.

8. Systematic exploration and uncertainty dominate young children's choices.