Parkes, David C.

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). Download

Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, Yang Liu, and David C. Parkes. 2020. “How do fairness definitions fare? testing public attitudes towards three algorithmic definitions of fairness in loan allocations.” Artificial Intelligence, 283, 103238. Download

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. Download

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. Download

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. Download

Nir Rosenfeld, Anna Hilgard, Sai S. Ravindranath, and David C. Parkes. 2020. “From predictions to decisions: Using lookahead regularization.” In In Annual Conference on Neural Information Processing Systems, NeurIPS '20. Download

Michael Neuder, Daniel J. Moroz, Rithvik Rao, and David C. Parkes. 2020. “Defending against malicious reorgs in tezos proof-of-stake.” In AFT ’20: 2nd ACM Conference on Advances in Financial Technologies (ACM '20), Pp. 46–58. Download

Sarah Keren, Sara Bernardini, Kofi Kwapong, and David C. Parkes. 2020. “Reasoning about plan robustness versus plan cost for partially informed agents.” In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning, KR 2020, Pp. 550–559. Download

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. Download

Paul Tylkin, Goran Radanovic, and David C. Parkes. 2020. “Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments.” In NeurIPS 2020 workshop on Cooperative AI. Download

Daniel J. Moroz, Daniel J. Aronoff, Neha Narula, and David C. Parkes. 2020. “Double-Spend Counterattacks: Threat of Retaliation in Proof-of-Work Systems.” CoRR abs/2002.10736 . Download

Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, and Yang Liu. 2020. “How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations.” Artificial Intelligence, 283, 103238 . Download

Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik, Melvin Gruesbeck, David C. Parkes, and Richard Socher. 2020. “Improving Equality and Productivity with AI-Driven Tax Policies.” CoRR abs/2004.13332 . Download

Rose E. Wang, Sarah A. Wu, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, and Max Kleiman-Weiner. 2020. “Too Many Cooks: Coordinating Multi-agent Collaboration Through Inverse Planning (Extended Abstract).” In Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), Pp. 2032-2034. Download

Hau Chan, David C. Parkes, and Karim R. Lakhani. 2020. “The Price of Anarchy of Self-Selection in Tullock Contests (Extended Abstract).” In , Proc. of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2020), Pp. 1795-1797. Download