Sai S. Ravindranath, Zhe Feng, Shira Li, Jonathan Ma, Scott Duke Kominers, and David C. Parkes. 8/2022. “
Deep Learning for Two-Sided Matching.” In 6th workshop in an interdisciplinary and international workshop series on matching under preferences. Vienna, Austria.
Mira Finkelstein, Nitsan Levy Schlot, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenschein, and Sarah Keren. 2022. “
Explainable Reinforcement Learning via Model Transforms. .” In Conference on Neural Information Processing Systems. NeurIPS 2022.
Stephan Zheng, Alexander Trott, Sunil Srinivasa, David C. Parkes, and Richard Socher. 2022. “
The AI Economist: Taxation policy design via two-level deep multiagent reinforcement learning.” Science Advances, 8, 18, Pp. eabk2607.
Download Ignacio Palacios-Huerta, David C. Parkes, and Richard Steinberg. 2022. “
Combinatorial Auctions in Practice.” Economics Literature .
Download Matthias Gerstgrasser, Rakshit Trivedi, and David C. Parkes. 2022. “
CrowdPlay: Crowdsourcing human demonstrations for offline learning.” In International Conference on Learning Representations (ICLR) 2022.
Download Zhou Fan, Francisco J. Marmolejo Cossío, Ben Altschuler, He Sun, Xintong Wang, and David C. Parkes. 2022. “
Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design.” In Proc. of Association for Computing Machinery (ACM) International Conference on Artificial Intelligence in Finance (ICAIF) , Pp. 9-17 .
Mira Finkelstein, Nitsan Levy Schlot, Lucy Liu, Yoav Kolumbus, David C. Parkes, Jeffrey S. Rosenschein, and Sarah Keren. 2022. “
Explainable Reinforcement Learning via Model Transforms.” In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS) .