Author: Robert Woods

Complexity permeates daily life. We study two types of complexity: (i) computational complexity, i.e., situations where it’s hard to figure out what to do, even if one has all the data (even the best electronic computers have a hard time dealing with this type of complexity; unsurprisingly, it has been studied extensively in computer science);…

Probabilistic uncertainty refers to situations where learning can proceed by repeatedly trying actions. Beliefs converge to a common standard (“objective probabilities”) regardless of how sophisticated belief updating takes place. This is also the environment where machine learning is successful. Probabilistic uncertainty is the foundation of much of empirical work on decision-making under uncertainty. Economists study…