Im Rahmen des Kolloquiums des Graduiertenkollegs Algorithmic Optimization findet am
Montag, dem 17. Juli 2023
16:00 Uhr c.t.
folgender Vortrag statt:
Learn-and-Play: Data, Agents, and Interactions
Dr. Gabriele Dragotto, Princeton University
How should an energy company determine its optimal production schedule? How should transport authorities design transportation networks? How should graduate students from medical schools be matched with residency training? In all these contexts, decision-making is rarely an individual task; on the contrary, it often involves the mutual interaction of several self-interested decision-makers deciding by solving optimization problems. However, the agents' selfdriven behavior often conflicts with the greater societal goals; in such cases, external regulators (e.g., governments) can intervene in the agents' interaction via incentives, laws, and regulations. This talk provides a method for learning the agents' preferences from data to design prescriptive interventions that possibly improve social welfare