Artificial Intelligence

2020
Sarah Keren, Haifeng Xu, Kofi Kwapong, David C. Parkes, and Barbara Grosz. 2020. “Information Shaping for Enhanced Goal Recognition of Partially-Informed Agents.” In Proceedings of 34th AAAI Conference on Artificial Intelligence (AAAI-2020). Download
2019
Berk Ustun, Alexander Spanghler, and Yang Liu. 2019. “Actionable Recourse in Linear Classification.” In ACM Conference on Fairness, Accountability, and Transparency (FAT '19). Download
Gregory D. Hager, Ann W. Drobnis, Fei Fang, Rayid Ghani, Amy Greenwald, Terah Lyons, David C. Parkes, Jason Schultz, Suchi Saria, Stephen F. Smith, and Milind Tambe. 2019. Artificial Intelligence for Social Good. Download
Jack Serrino, Max Kleiman-Weiner, David C. Parkes, and Joshua B. Tenenbaum. 2019. “Finding Friend and Foe in Multi-Agent Games.” In Proceedings of the 32nd Annual Conf. on Neural Information Processing Systems 2019, (NeurIPS 2019), Pp. 1249-1259. Download
Thanh H. Nguyen and Haifeng Xu. 2019. “Imitative Attacker Deception in Stackelberg Security Games.” In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019). Download
Jiarui Gan, Haifeng Xu, Qingyu Guo, Long Tran-Thanh, Zinovi Rabinovich, and Michael Wooldridge. 2019. “Imitative Follower Deception in Stackelberg Games.” In Proceedings of the 20th ACM Conference on Economics and Computation (EC'19). Download
Iyad Rahwan, Manuel Cebrian, Nick Obradovich, Josh Bongard, Jean-François Bonnefon, Cynthia Breazeal, Jacob W. Crandall, Nicholas A. Christakis, Iain D. Couzin, Matthew O. Jackson, Nicholas R. Jennings, Ece Kamar, Isabel M. Kloumann, Hugo Larochelle, David Lazer, Richard McElreath, Alan Mislove, David C. Parkes, Alex ‘Sandy’ Pentland, Margaret E. Roberts, Azim Shariff, Joshua B. Tenenbaum, and Michael Wellman. 2019. “Machine behaviour.” Nature, 568, Pp. 477-486. Download
Yiling Chen, Yang Liu, and Juntao Wang. 2019. “Randomized Wagering Mechanisms.” In Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19) . Download
Sarah Keren, Gopal K. Vashishtha, and David C. Parkes. 2019. “Reinforcement Learning Design.” In ICAPS 2019 Workshop on Reasoning about Actions and Processes: Highlights of Recent Advances (RAC-ICAPS 2019).
2018
Lily Hu. 2018. “Justice Beyond Utility in Artificial Intelligence.” Artificial Intelligence, Ethics, and Society. (AIES 2018). Download
Goran Radanovic, Adish Singla, Andreas Krause, and Boi Faltings. 2018. “Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints.” In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18). Download
Goran Radanovic and Boi Faltings. 2018. “Partial Truthfulness in Minimal Peer Prediction Mechanisms with Limited Knowledge.” In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI'18). Download
Reshef Meir and David C. Parkes. 2018. “Playing the Wrong Game: Bounding Externalities in Diverse Populations of Agents.” In Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS '18), Pp. 86-94. Download
Lily Hu and Yiling Chen. 2018. “A Short-term Intervention for Long-term Fairness in the Labor Market.” In Proceedings of the 27th International Conference on World Wide Web. (WWW 2018). Download
Yiling Chen, Chara Podimata, Ariel D. Procaccia, and Nisarg Shah. 2018. “Strategyproof Linear Regression in High Dimensions.” In Proceedings of the 19th ACM Conference on Economics and Computation (EC'18). Download
2017
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, and David C. Parkes. 2017. “Calibrated fairness in Bandits.” In Proceedings of the 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning (Fat/ML 2017). Download
Yang Liu. 2017. “Fair Optimal Stopping Policy for Matching with Mediator.” In Proc. of the Conference on Uncertainty in Artificial Intelligence (UAI-2017). Download
Lily Hu and Yiling Chen. 2017. “Fairness at Equilibrium in the Labor Market.” In Workshop on Fairness, Accountability, and Transparency in Machine Learning. (FAT/ML 2017). Download
Boi Faltings and Goran Radanovic. 2017. Game Theory for Data Science: Eliciting Truthful Information. Morgan & Claypool Publishers.
Yang Liu and Yiling Chen. 2017. “Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices.” In Proc. of The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) . Download

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