Using a new machine learning algorithm, a team at the Technical University of Munich (TUM) has succeeded in analyzing complex markets and their equilibrium strategies. Until now, such analyses were limited to very simple auction markets. The new numerical method opens up new possibilities for economic theory and new applications as in wireless spectrum auctions, among others.
Life is a game – at least from the perspective of game theory. This branch of mathematics provides tools for describing the behavior of actors in strategic interactions and computing optimal behavioral responses. Applications extend from board games such as chess to the analysis of international climate negotiations. An important subfield of game theory is auction theory, which is used in economic theory to model markets. Several Nobel Prizes in Economic Sciences have been awarded in this area, most recently to Robert Wilson and Paul Milgrom in 2020.
Read more.Source: “Using machine learning to understand complex auctions”, TUM News
