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); (ii) inference complexity, i.e., situations in which it is hard, from observations, to infer what caused the observations. When making decisions under either type of complexity, one cannot generally be confident to be right. We (and others) have recently proposed that both types of uncertainty cause people not to try to maximise rewards/values, but to control surprise. Engineers have long used the idea as one way to ensure robust control.
Leverhulme International Professorship in Neuroeconomics at the University of Cambridge Faculty of Economics
