Dorsa Sadigh
Cited by
Cited by
On the opportunities and risks of foundation models
R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ...
arXiv preprint arXiv:2108.07258, 2021
Planning for autonomous cars that leverage effects on human actions.
D Sadigh, S Sastry, SA Seshia, AD Dragan
Robotics: Science and systems 2, 1-9, 2016
Reactive synthesis from signal temporal logic specifications
V Raman, A Donzé, D Sadigh, RM Murray, SA Seshia
Proceedings of the 18th international conference on hybrid systems …, 2015
Active preference-based learning of reward functions
D Sadigh, AD Dragan, S Sastry, SA Seshia
Towards verified artificial intelligence
SA Seshia, D Sadigh, SS Sastry
arXiv preprint arXiv:1606.08514, 2016
Information gathering actions over human internal state
D Sadigh, SS Sastry, SA Seshia, A Dragan
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016
Hierarchical game-theoretic planning for autonomous vehicles
JF Fisac, E Bronstein, E Stefansson, D Sadigh, SS Sastry, AD Dragan
2019 International conference on robotics and automation (ICRA), 9590-9596, 2019
A learning based approach to control synthesis of markov decision processes for linear temporal logic specifications
D Sadigh, ES Kim, S Coogan, SS Sastry, SA Seshia
53rd IEEE Conference on Decision and Control, 1091-1096, 2014
Multi-agent generative adversarial imitation learning
J Song, H Ren, D Sadigh, S Ermon
Advances in neural information processing systems 31, 2018
Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state
D Sadigh, N Landolfi, SS Sastry, SA Seshia, AD Dragan
Autonomous Robots 42, 1405-1426, 2018
Safe control under uncertainty with probabilistic signal temporal logic
D Sadigh, A Kapoor
Proceedings of Robotics: Science and Systems XII, 2016
Synthesis for human-in-the-loop control systems
W Li, D Sadigh, SS Sastry, SA Seshia
Tools and Algorithms for the Construction and Analysis of Systems: 20th …, 2014
Learning reward functions by integrating human demonstrations and preferences
M Palan, NC Landolfi, G Shevchuk, D Sadigh
arXiv preprint arXiv:1906.08928, 2019
Data-driven probabilistic modeling and verification of human driver behavior
D Sadigh, K Driggs-Campbell, A Puggelli, W Li, V Shia, R Bajcsy, ...
AAAI Spring Symposium-Technical Report, 56-61, 2014
Automating exercise generation: A step towards meeting the MOOC challenge for embedded systems
D Sadigh, SA Seshia, M Gupta
Proceedings of the workshop on embedded and cyber-physical systems education …, 2012
Learning latent representations to influence multi-agent interaction
A Xie, D Losey, R Tolsma, C Finn, D Sadigh
Conference on robot learning, 575-588, 2021
Asking easy questions: A user-friendly approach to active reward learning
E Bıyık, M Palan, NC Landolfi, DP Losey, D Sadigh
arXiv preprint arXiv:1910.04365, 2019
Batch active preference-based learning of reward functions
E Biyik, D Sadigh
Conference on robot learning, 519-528, 2018
When humans aren't optimal: Robots that collaborate with risk-aware humans
M Kwon, E Biyik, A Talati, K Bhasin, DP Losey, D Sadigh
Proceedings of the 2020 ACM/IEEE international conference on human-robot …, 2020
Efficient and trustworthy social navigation via explicit and implicit robot–human communication
Y Che, AM Okamura, D Sadigh
IEEE Transactions on Robotics 36 (3), 692-707, 2020
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