Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 0 |
| Since 2007 (last 20 years) | 6 |
Descriptor
| Bayesian Statistics | 6 |
| Learning | 6 |
| Experiments | 3 |
| Models | 3 |
| Prediction | 3 |
| Classification | 2 |
| Inferences | 2 |
| Statistical Inference | 2 |
| Anxiety | 1 |
| Bias | 1 |
| Change | 1 |
| More ▼ | |
Author
Publication Type
| Journal Articles | 6 |
| Reports - Evaluative | 3 |
| Reports - Research | 3 |
Education Level
| Preschool Education | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Griffiths, Thomas L.; Lewandowsky, Stephan; Kalish, Michael L. – Cognitive Science, 2013
Information changes as it is passed from person to person, with this process of cultural transmission allowing the minds of individuals to shape the information that they transmit. We present mathematical models of cultural transmission which predict that the amount of information passed from person to person should affect the rate at which that…
Descriptors: Culture, Information Dissemination, Mathematical Models, Prediction
Austerweil, Joseph L.; Griffiths, Thomas L. – Cognitive Psychology, 2011
Most psychological theories treat the features of objects as being fixed and immediately available to observers. However, novel objects have an infinite array of properties that could potentially be encoded as features, raising the question of how people learn which features to use in representing those objects. We focus on the effects of…
Descriptors: Visual Stimuli, Novelty (Stimulus Dimension), Bayesian Statistics, Learning
Sanborn, Adam N.; Griffiths, Thomas L.; Navarro, Daniel J. – Psychological Review, 2010
Rational models of cognition typically consider the abstract computational problems posed by the environment, assuming that people are capable of optimally solving those problems. This differs from more traditional formal models of cognition, which focus on the psychological processes responsible for behavior. A basic challenge for rational models…
Descriptors: Models, Cognitive Processes, Psychology, Monte Carlo Methods
Griffiths, Thomas L.; Christian, Brian R.; Kalish, Michael L. – Cognitive Science, 2008
Many of the problems studied in cognitive science are inductive problems, requiring people to evaluate hypotheses in the light of data. The key to solving these problems successfully is having the right inductive biases--assumptions about the world that make it possible to choose between hypotheses that are equally consistent with the observed…
Descriptors: Logical Thinking, Bias, Identification, Research Methodology
Goodman, Noah D.; Tenenbaum, Joshua B.; Feldman, Jacob; Griffiths, Thomas L. – Cognitive Science, 2008
This article proposes a new model of human concept learning that provides a rational analysis of learning feature-based concepts. This model is built upon Bayesian inference for a grammatically structured hypothesis space--a concept language of logical rules. This article compares the model predictions to human generalization judgments in several…
Descriptors: Mathematics Education, Concept Formation, Models, Prediction
Schulz, Laura E.; Bonawitz, Elizabeth Baraff; Griffiths, Thomas L. – Developmental Psychology, 2007
Causal learning requires integrating constraints provided by domain-specific theories with domain-general statistical learning. In order to investigate the interaction between these factors, the authors presented preschoolers with stories pitting their existing theories against statistical evidence. Each child heard 2 stories in which 2 candidate…
Descriptors: Inferences, Young Children, Bayesian Statistics, Story Telling

Peer reviewed
Direct link
