TY - JOUR AU - Heidekrüger, Stefan PY - 2022/06/28 Y2 - 2024/03/28 TI - Equilibrium Learning in Auction Markets JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 36 IS - 11 SE - The Twenty - Seventh AAAI / SIGAI Doctoral Consortium DO - 10.1609/aaai.v36i11.21578 UR - https://ojs.aaai.org/index.php/AAAI/article/view/21578 SP - 12882-12883 AB - My dissertation investigates the computation of Bayes-Nash equilibria in auctions via multiagent learning. A particular focus lies on the game-theoretic analysis of learned gradient dynamics in such markets. This requires overcoming several technical challenges like non-differentiable utility functions and infinite-dimensional strategy spaces. Positive results may open the door for wide-ranging applications in Market Design and the economic sciences. ER -