2017 Publications
1. R. Jia, R. Dong,
P. Ganesh, S. S. Sastry, C. Spanos.
Towards a Theory of Free-Lunch Privacy in
Cyber-Physical Systems. In the 55th Annual Allerton Conference on Communication, Control, and
Computing, 2017.
2. T. Westenbroek, R. Dong, L. J. Ratliff, S. S. Sastry. Statistical
Estimation in Competitive Settings with Strategic Data Sources. In the IEEE 56th Conference on Decision and Control
(CDC), 2017.
3. R. Jia, R. Dong,
S. S. Sastry, C. Spanos. Optimal Sensor-Controller Codesign for Privacy in Dynamical Systems. In the IEEE 56th Conference on Decision and Control
(CDC), 2017.
4. D. Calderone, R. Dong, S. S. Sastry.
External-Cost Wardrop
Equilibria in Routing Games. In the IEEE 20th International Conference on Intelligent Transportation Systems
(ITSC), 2017.
5. R. Jia, R. Dong,
S. S. Sastry, C. J. Spanos.
Privacy-Enhanced Architecture for
Occupancy-based HVAC Control. In the 8th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS),
2017.
6. Dorsa Sadigh, Anca D. Dragan, S. Shankar Sastry, Sanjit A.
Seshia. Active Preference-Based Learning
of Reward Functions. Proceedings of Robotics: Science and Systems (RSS),
July 2017. [PDF]
7. Negar Mehr, Dorsa Sadigh, Roberto Horowitz, S. Shankar Sastry,
Sanjit A. Seshia. Stochastic Predictive Freeway Ramp Metering
from Signal Temporal Logic Specifications. Proceedings of the American
Control Conference, May 2017. [PDF]
8. Eric Mazumdar, Roy
Dong, Vicenc
Rubies Royo,
Claire
Tomlin, S.
Shankar Sastry.
A Multi-Armed Bandit Approach for Online
Expert Selection in Markov Decision Processes. arXiv:1707.05714v1 [cs.SY]
18 Jul 2017. [PDF]
9. Ioannis Konstantakopoulos,
Lillian J. Ratliff, Ming Jin, S. Shankar Sastry, and Costas Spanos. A
Robust Utility Learning Framework via Inverse Optimization. IEEE Transactions on Control Systems
Technology, PP(99):1--17, 2017.
10. Kamil Nar, Lillian J. Ratliff, and S. Shankar Sastry. Learning Prospect Theory Value Function and Reference
Point of a Sequential Decision Maker. In Proceedings of the 56th IEEE Confefence on
Decision and Control, 2017.
11. Eric Mazumdar, Lillian J.
Ratliff, Tanner Fiez, and S. Shankar Sastry. Gradient--Based Inverse Risk-Sensitive
Reinforcement Learning with Applications. In Proceedings of the 56th IEEE Confefence on
Decision and Control, 2017.
12. Jaime F. Fisac, Monica A. Gates,
Jessica B. Hamrick, Chang Liu, Dylan Hadfield-Menell,
Malayandi Palaniappan, Dhruv Malik, S. Shankar Sastry,
Thomas L. Griffiths, and Anca D. Dragan. Pragmatic-Pedagogic Value Alignment. ISRR 2017. [PDF]