Publications

A Game-Theoretic Approach for Hierarchical Policy-Making, Feiran Jia, Aditya Mate, Zun Li, Shahin Jabbari, Mithun Chakraborty, Milind Tambe, Michael Wellman and Yevgeniy Vorobeychik, 2nd International (Virtual) Workshop on Autonomous Agents for Social Good, AASG 2021, accepted.

Resource Pooling for Shared Fate: Incentivizing Effort in Interdependent Security Games through Cross-investments, Mohammadmahdi Khalili, Xueru Zhang, and Mingyan Liu, IEEE Transactions on Control of Network Systems (TCNS), December, 2020.

Robust Spatial-Temporal Incident Prediction, Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, Yevgeniy Vorobeychik, Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020.

Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations, Lily Xu, Shahrzad Gholami, Sara McCarthy, Bistra Dilkina, Andrew Plumptre, Milind Tambe, Rohit Singh, Mustapha Nsubuga, Joshua Mabonga, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Tom Okello, Eric Enyel, 36th IEEE International Conference on Data Engineering (ICDE), 2020.

Scalable Game-Focused Learning of Adversary Models: Data-to-Decisions in Network Security Games, Kai Wang, Andrew Perrault, Aditya Mate, Milind Tambe, International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020.

Who and When to Screen: Multi-Round Active Screening for Network Recurrent Infectious Diseases Under Uncertainty, Han-Ching Ou, Arunesh Sinha, Sze-Chuan Suen, Andrew Perrault, Alpan Raval, Milind Tambe,  International Conference on Autonomous Agents and Multi-Agent Systems ( AAMAS), 2020.

End-to-End Game-Focused Learning of Adversary Behavior in Security Games, Andrew Perrault, Bryan Wilder, Eric Ewing, Aditya Mate, Bistra Dilkina, Milind Tambe, Thirty-fourth AAAI Conference on Artificial Intelligence, 2020.

MIPaaL: Mixed Integer Program as a Layer, Aaron Ferber, Bryan Wilder, Bistra Dilkina, Milind Tambe, Thirty-fourth AAAI Conference on Artificial Intelligence, 2020.

End to end learning and optimization on graphs, Bryan Wilder, Eric Ewing, Bistra Dilkina, Milind Tambe, Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019.

Impact of Social Distancing During Covid-19 Pandemic on Crime in Los Angeles and Indianapolis, Mohler, George and Bertozzi, Andrea L. and Carter, Jeremy and Short, Martin B. and Sledge, Daniel and Tita, George E. and Uchida, Craig D. and Brantingham, P. Jeffrey, Journal of Criminal Justice, vol. 68, pp. 101692, 2020.

Fitting in and breaking up: A nonlinear version of coevolving voter models, Yacoub H. Kureh and Mason A. Porter, Physical Review E, 101 (6), pp. 062303-062325, June 2020.

Robust Spatial-Temporal Incident Prediction, Ayan Mukhopadhyay, Kai Wang, Andrew Perrault, Mykel Kochenderfer, Milind Tambe, and Yevgeniy Vorobeychik, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR volume 124, 2020.

Robust Collective Classification against Structural Attacks, Kai Zhou and Yevgeniy Vorobeychik, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR volume 124, 2020.

Defending Against Physically Realizable Attacks on Image Classification, Tong Wu, Liang Tong, and Yevgeniy Vorobeychik, International Conference on Learning Representations (ICLR), 2020.

Deception through half-truths, Andrew Estornell, Sanmay Das, and Yevgeniy Vorobeychik, AAAI Conference on Artificial Intelligence, 2020.

Computing equilibria in binary networked public goods games, Sixie Yu, Kai Zhou, Jeffrey Brantingham, and Yevgeniy Vorobeychik, AAAI Conference on Artificial Intelligence, 2020.

Adversarial Robustness of Similarity-Based Link Prediction, Kai Zhou, Tomasz Michalak, and Yevgeniy Vorobeychik, IEEE International Conference on Data Mining (ICDM), 2019.

Approximation Algorithms for Coordinating Ad Campaigns on Social Networks, Kartik Lakhotia and David Kempe, ACM International Conference on Information and Knowledge Management (CIKM), 2019.

Interactive Learning of a Dynamic Structure, Ehsan Emamjomeh-Zadeh, David Kempe, Mohammad Mahdian, Rob Schapire, International Conference on Algorithmic Learning Theory (ALT), 2020.

Games on Networks with Community Structure: Existence, Uniqueness and Stability of Equilibria, Kun Jin, Mohammadmahdi Khalili, and Mingyan Liu, American Control Conference (ACC), July 2020.

Structure learning for approximate solution of many-player games, Zun Li and Michael P. Wellman, 34th AAAI Conference on Artificial Intelligence, February 2020.

Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization, Bryan Wilder, Bistra Dilkina, and Milind Tambe. Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) Conference, 2019.

Don’t Put All Your Strategies in One Basket: Playing Green Security Games with Imperfect Prior Knowledge, Shahrzad Gholami, Amulya Yadav, Long Tran-Thanh, Bistra Dilkina, and Milind Tambe, Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, Pp. 395–403, 2019.

Deep Fictitious Play for Games with Continuous Action Spaces, Nitin Kamra, Umang Gupta, Kai Wang, Fei Fang, Yan Liu, and Milind Tambe, “Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems,” Pp. 2042–2044, 2019.

Learning to Prescribe Interventions for Tuberculosis Patients, Jackson A. Killian, Bryan Wilder, Amit Sharma, Vinod Choudhary, Bistra Dilkina, and Milind Tambe, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-19), 2019.

Integrating optimization and learning to prescribe interventions for tuberculosis patients, Bryan Wilder, Jackson A. Killian, Amit Sharma, Vinod Choudhary, Bistra Dilkina, and Milind Tambe, 10th International Workshop on Optimization in Multiagent Systems (OptMAS), 2019. 

Group-Fairness in Influence Maximization, Alan Tsang, Bryan Wilder, Eric Rice, Milind Tambe, and Yair Zick, International Joint Conference on Artificial Intelligence,” 2019. [PDF]

Attacking Similarity-Based Link Prediction in Social Networks, Kai Zhou, Tomasz P. Michalak, Talal Rahwan, Marcin Waniek, Yevgeniy Vorobeychik, Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019. 

Incentivizing Collaboration in a Competition, Arunesh Sinha, Michael P. Wellman, Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019. 

Removing Malicious Nodes from Networks, Sixie Yu, Yevgeniy Vorobeychik, Proc. of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019. 

Generative Graph Models based on Laplacian Spectra, Alana Shine, David Kempe, International World Wide Web Conference Committee, May 2019. 

Defending Elections Against Malicious Spread of Misinformation, Bryan Wilder, Yevgeniy Vorobeychik, Association for the Advancement of Artificial Intelligence (AAAI), January 2019.