Compositional inductive biases in human function learning

Samuel J. Gershman
Harvard University
January 14, 2020
This talk presents evidence that humans learn complex functions by harnessing compositionality: complex structure is decomposed into simpler building blocks. I formalize this idea in the framework of Bayesian nonparametric regression using a grammar over Gaussian process kernels, and compare this approach with other structure learning approaches. People consistently chose compositional (over non-compositional) extrapolations and interpolations of functions.