High Dimensional Calibration for Rational Decision Making

Explore a 29-minute lecture on high dimensional calibration for rational decision making, presented by Aaron Roth from the University of Pennsylvania at the Simons Institute. Delve into the properties that high dimensional forecasts must possess to incentivize downstream decision makers to respond optimally, as if the forecasts were accurate. Examine the feasibility of efficiently generating such forecasts in high dimensional strategic settings. Discover new algorithms for learning in games with large action spaces and gain insights into prior-free results in sequential principal agent games. Enhance your understanding of statistical forecasts and their impact on rational decision making in complex environments.