Crash Course in Decision Theory: Ideas and Problems in Decision Making Under Uncertainty

Explore key concepts in decision theory and their applications in this 58-minute coffee talk by Massimiliano Amarante from Université de Montréal. Dive into the main ideas of decision making under uncertainty, including Expected Utility (EU), Maxmin EU, Choquet EU, the Invariant bi-separable model, and the Variational model. Discover how these concepts relate to real-world challenges such as one-shot learning, learning with corrupted data, robust statistics, fuzzy systems, climate change, and finance. Gain insights into the difficulties of extending non-Bayesian models to dynamic settings, preparing you for a deeper understanding of decision-making processes in various fields.

Part 1: Crash Course in Decision Theory: Ideas and Problems in Decision Making Under Uncertainty