Erie Boorman

How do we make decisions? How do we learn from their outcomes? Professor Boorman seeks mechanistic answers to such questions at the behavioral, computational, and neural systems levels. His research is multi-disciplinary, lying at the intersection between psychology, neuroscience, artificial intelligence, and behavioral economics. His lab investigates how the adult human brain forms and tunes predictive models of the environment, and how it leverages these models to make decisions. The prediction problems he investigates span reward prediction (e.g. money, foods, etc.), social prediction (e.g. other people’s intentions, traits, etc.), and “state” prediction (e.g. perceptually signaled and inferred latent contexts).

Current research topics include cognitive maps and inferences, causal learning, structure learning, domain generality of prediction and selection systems, and behavioral adaptation.

For more information on the research we do, see our lab website.