A rational model of preference learning and choice prediction by children
Lucas, Christopher G., Griffiths, Thomas L., Xu, Fei, Fawcett, Christine
–Neural Information Processing Systems
Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what children are doing when they learn about preferences or how they use that knowledge. We use a rational model of preference learning, drawing on ideas from economics and computer science, to explain the behavior of children in several recent experiments. Specifically, we show how a simple econometric model can be extended to capture two- to four-year-oldsâ use of statistical information in inferring preferences, and their generalization of these preferences.
Neural Information Processing Systems
Dec-31-2009
- Country:
- North America
- Canada > Ontario
- Toronto (0.14)
- United States > California
- Alameda County > Berkeley (0.14)
- San Francisco County > San Francisco (0.14)
- Canada > Ontario
- North America
- Genre:
- Research Report > New Finding (0.46)
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