Paul Tylkin, Goran Radanovic, and David C. Parkes. 2021. “
Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments.” In Proc. 20th Int. Conf. on Auton. Agents and Multiagent Systems (AAMAS), Pp. 1686-1688 .
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, and Mitchell Stern. 2021. “
Dynamic posted-price mechanisms for the blockchain transaction-fee market.” In AFT 2021, Pp. 86-99.
Mark York, Munther Dahleh, and David C. Parkes. 2021. “
Eliciting Social Knowledge for Creditworthiness Assessment.” In Proc. 17th Conference on Web and Internet Economics , Pp. 428-445.
Sophie Hilgard, Nir Rosenfeld, Mahzarin R. Banaji, Jack Cao, and David C. Parkes. 2021. “
Learning Representations by Humans.” In ICML 2021, Pp. 4227-4238.
Gianluca Brero, Darshan Chakrabarti, Alon Eden, Matthias Gerstgrasser, Vincent Li, and David C. Parkes. 2021. “
Learning Stackelberg Equilibria in Sequential Price Mechanisms.” In . Proc. ICML Workshop for Reinforcement Learning Theory.
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.
David Parkes. 2021. “
Playing with symmetry with neural networks.” Nature Machine Intelligence , 3, 8, Pp. 658-658.
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), Pp. 5219-5227.
Sarah A. Wu, Rose E. Wang, James A. Evans, Joshua B. Tenenbaum, David C. Parkes, and Max Kleiman-Weiner. 2021. “
Too Many Cooks: Bayesian Inference for Coordinating Multi-Agent Collaboration.” Topics Cognitive Science , 13, 2, Pp. 2032-2034.
Vincent Conitzer, Zhe Feng, David C. Parkes, and Eric Sodomka. 2021. “
Welfare-Preserving ε-BIC to BIC Transformation with Negligible Revenue Loss.” In , Pp. 76-94. Proceedings 17th Conference on Web and Internet Economics (WINE).