Charley M. Wu

The paper shows that asymmetric learning, where beliefs about winners or losers are updated selectively, improves transitive inference in humans and aligns with cognitive distortions observed in psychophysics and behavioral economics.

The paper tests if computational principles of spatial search apply to conceptual search using a Gaussian Process model and finds similar but distinct generalization patterns.

The paper shows that information sharing can benefit individuals through pseudo-reciprocity in simulations of competitive environments, even without explicit reciprocation.

This study introduces a spatially correlated multi-armed bandit task to model how people form beliefs about unexplored payoffs and guide search behavior based on spatial correlations.