A rational model of preference learning and choice prediction by children

Part of Advances in Neural Information Processing Systems 21 (NIPS 2008)

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Christopher Lucas, Thomas Griffiths, Fei Xu, Christine Fawcett


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.