Samuel J. Gershman

The paper shows that reference points in decision making are discovered through Bayesian structure learning, with changes in outcome distributions inducing new reference points and affecting risk preferences.

The paper shows people balance mental simulations and physical experiments to learn action effects, adjusting effort based on trial characteristics.

The paper demonstrates that people use amortized inference strategies when answering related queries, caching summary statistics rather than raw samples.