COGS 343 Probabilistic Models of Cognition

Probabilistic models have increasingly been applied to understand how the mind works across domains such as motor control decision-making and causal inference. We will learn how such models work learning the mathematical tools necessary to implement them such as Bayesian inference graphical models and Markov models. We will consider both how human cognition can inform machine learning and how computational approaches can lead to new ideas about cognition.