Payam Piray
Assistant Professor
Department of Psychology and Neuroscience
University of Southern California
Adaptive learning requires distinguishing two causes of uncertainty, moment-to-moment stochasticity in observations and environmental volatility, that demand opposite adjustments to learning rate. Yet both increase experienced noise, making their dissociation computationally difficult and prone to systematic errors. I will present a computational framework, behavioral paradigm, and large-scale data investigating how humans dissociate these two sources of noise, and how this process gives rise to two kinds of learning failure.
View a recording of this session here.