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How do people actively learn functional rules, i.e. a mapping of continuous inputs onto a continuous output? We investigate information search behavior in a multiple-featurefunction learning task in which participants either actively select or passively receive observations. We find that participants benefit from actively selecting information, inparticular in their function extrapolation performance. By introducing and comparing different models of active function learning, we find thatdoi:10.31234/osf.io/wqf4u fatcat:brusa5isf5gbvledn2ipksrowa