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2008 NeurIPS NeurIPS 2008

A rational model of preference learning and choice prediction by children

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-olds’ use of statistical information in inferring preferences, and their generalization of these preferences.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Interdisciplinary
📈 Trend Setter - Decision Making
🧭 Keyword Pioneer - statistical inference
🐣 Hot Topic Early Bird - preference learning

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