Economics

Working Paper
Barton E. Lee, Daniel J. Moroz, and David C. Parkes. Working Paper. “An Analysis of Blockchain Governance via Political Economics”.
Ignacio Palacios-Huerta, David C. Parkes, and Richard Steinberg. Working Paper. “Combinatorial Auctions in Practice”. SSRN
Hongyao Ma, Reshef Meir, David C. Parkes, and Elena Wu-Yan. Working Paper. “Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present Bias”. arXiv
2022
Zhe Feng, David C. Parkes, and Sai Srivatsa Ravindranath. 2022. “Machine Learning for Matching Markets.” In Online matching theory and market design. N. Immorlica, F. Echenique, and V. Vazirani (eds), Cambridge University Press.
2021
Stephan Zheng, Alexander Trott, Sunil Srinivasa, Richard Socher, and David C. Parkes. 2021. “The AI Economist: Optimal Economic Policy Design via Two-level Deep Reinforcement Learning.” CoRR abs/2004.13332.
Paul Duetting, Zhe Feng, Hari Narasimhan, David C. Parkes, and Sai Srivatsa Ravindranath. 2021. “Optimal auctions through deep learning.” Communications of the ACM, 64, 8, Pp. 109-116.
Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, and Duncan Rheingans-Yoo. 2021. “Reinforcement Learning of Simple Indirect Mechanisms.” In The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21).
Hongyao Ma, Fei Fang, and David C. Parkes. 2021. “Spatio-temporal pricing for ridesharing platforms.” Operations Research .
Vincent Conitzer, Zhe Feng, David C. Parkes, and Eric Sodomka. 2021. “Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss.” In . Proceedings 17th Conference on Web and Internet Economics (WINE).
2020
Haris Aziz, Hau Chan, Barton E. Lee, and David C. Parkes. 2020. “The capacity constrained facility location problem.” Games Econ. Behavior, 124:478–490, Pp. 478-490.
Zhe Feng, David C. Parkes, and Haifeng Xu. 2020. “The intrinsic robustness of stochastic bandits to strategic manipulation.” In Proceedings of the 37th International Conference on Machine Learning, ICML ’20, 119: Pp. 3092-3101. Proceedings of Machine Learning Research.
Paul Duetting, Zhe Feng, Harikrishna Narasimhan, David C. Parkes, and Sai S. Ravindranath. 2020. “Optimal auctions through deep learning.” Communications of the ACM, 63, 12.
Hongyao Ma, Reshef Meir, David C. Parkes, and Elena Wu-Yan. 2020. “Penalty Bidding Mechanisms for Allocating Resources and Overcoming Present-Bias.” In , Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), Pp. 807-815.
Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, and Duncan Rheingans-Yoo. 2020. “Reinforcement learning of simple indirect mechanisms.” In NeurIPS’20 Workshop on Machine learning for Economic Policy.
2019
David C. Parkes and Rakesh V. Vohra. 2019. Algorithmic and Economic Perspectives on Fairness.
Hongyao Ma, Reshef Meir, David C. Parkes, and James Zou. 2019. “Contingent Payment Mechanisms for Resource Utilization.” In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS), Pp. 422-430.
Paul Duetting, Felix A. Fischer, and David C. Parkes. 2019. “Expressiveness and Robustness of First-Price Position Auctions.” Mathematics of Operations Research, 44, 1, Pp. 196-211.
Paul Duetting, Zhe Feng, Harikrishna Narasimham, David C. Parkes, and Sai S. Ravindranath. 2019. “Optimal Auctions through Deep Learning.” In Proceedings of the 36th International Conference on Machine Learning (ICML’19), Pp. 1706-1715.
Duncan Rheingans-Yoo, Scott Duke Kominers, Hongyao Ma, and David C. Parkes. 2019. “Ridesharing with Driver Location Preferences.” In Proceedings of the 28th Int. Joint Conf. on Artificial Intelligence, (IJCAI 2019), Pp. 557-564.
Hongyao Ma, Fei Fang, and David C. Parkes. 2019. “Spatio-Temporal Pricing for Ridesharing Platforms.” In Proceedings of the 20th ACM Conference on Economics and Computation (EC’19), Pp. 583.

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