ELSC Seminar Series

Many models in cognitive neuroscience suggest that the mind operates in optimal, or near-optimal, manner. Bayesian models, in particular, often aim to show that perception, learning, decision-making and other functions are optimal, when seen as inferences under uncertainty. But what force does optimality carry – what does the appeal to optimality explain, and when? My talk will explore this question, focusing especially on Bayesian models. I suggest that we should distinguish merely methodological from substantive appeals to optimality. Then, I discuss conditions that need to be in place for optimality-based analyses to carry explanatory weight.