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2020 – today
- 2024
[j18]Erdem Biyik
, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active preference-based Gaussian process regression for reward learning and optimization. Int. J. Robotics Res. 43(5): 665-684 (2024)- [j17]Jason M. O'Kane, Michael W. Otte, Dorsa Sadigh, Pratap Tokekar:
Selected papers from WAFR 2022. Int. J. Robotics Res. 43(9): 1281-1282 (2024) - [j16]Erdem Biyik, Nima Anari, Dorsa Sadigh:
Batch Active Learning of Reward Functions from Human Preferences. ACM Trans. Hum. Robot Interact. 13(2): 24:1-24:27 (2024) - [c122]Boyuan Chen, Zhuo Xu, Sean Kirmani, Brian Ichter, Dorsa Sadigh, Leonidas J. Guibas, Fei Xia:
SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities. CVPR 2024: 14455-14465 - [c121]Karthik Mahadevan, Jonathan Chien, Noah Brown, Zhuo Xu, Carolina Parada, Fei Xia, Andy Zeng, Leila Takayama, Dorsa Sadigh:
Generative Expressive Robot Behaviors using Large Language Models. HRI 2024: 482-491 - [c120]Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh:
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. ICLR 2024 - [c119]Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter:
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. ICML 2024 - [c118]Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, Dorsa Sadigh:
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models. ICML 2024 - [c117]Montserrat Gonzalez Arenas, Ted Xiao, Sumeet Singh, Vidhi Jain, Allen Z. Ren, Quan Vuong, Jake Varley, Alexander Herzog, Isabel Leal, Sean Kirmani, Mario Prats, Dorsa Sadigh, Vikas Sindhwani, Kanishka Rao, Jacky Liang, Andy Zeng:
How to Prompt Your Robot: A PromptBook for Manipulation Skills with Code as Policies. ICRA 2024: 4340-4348 - [c116]Minae Kwon, Hengyuan Hu, Vivek Myers, Siddharth Karamcheti, Anca D. Dragan, Dorsa Sadigh:
Toward Grounded Commonsense Reasoning. ICRA 2024: 5463-5470 - [c115]Abby O'Neill, Abdul Rehman, Abhiram Maddukuri, Abhishek Gupta, Abhishek Padalkar, Abraham Lee, Acorn Pooley, Agrim Gupta, Ajay Mandlekar, Ajinkya Jain, Albert Tung, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Rai, Anchit Gupta, Andrew Wang, Anikait Singh, Animesh Garg, Aniruddha Kembhavi, Annie Xie, Anthony Brohan, Antonin Raffin, Archit Sharma, Arefeh Yavary, Arhan Jain, Ashwin Balakrishna, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Blake Wulfe, Brian Ichter, Cewu Lu, Charles Xu, Charlotte Le, Chelsea Finn, Chen Wang, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Christopher Agia, Chuer Pan, Chuyuan Fu, Coline Devin, Danfei Xu, Daniel Morton, Danny Driess, Daphne Chen, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dinesh Jayaraman, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Ethan Paul Foster, Fangchen Liu, Federico Ceola, Fei Xia, Feiyu Zhao, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Gilbert Feng, Giulio Schiavi, Glen Berseth, Gregory Kahn, Guanzhi Wang, Hao Su, Haoshu Fang, Haochen Shi, Henghui Bao, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Huy Ha, Igor Mordatch, Ilija Radosavovic, Isabel Leal, Jacky Liang, Jad Abou-Chakra, Jaehyung Kim, Jaimyn Drake, Jan Peters, Jan Schneider, Jasmine Hsu, Jeannette Bohg, Jeffrey Bingham, Jeffrey Wu, Jensen Gao, Jiaheng Hu, Jiajun Wu, Jialin Wu, Jiankai Sun, Jianlan Luo, Jiayuan Gu, Jie Tan, Jihoon Oh, Jimmy Wu, Jingpei Lu, Jingyun Yang, Jitendra Malik, João Silvério, Joey Hejna, Jonathan Booher, Jonathan Tompson, Jonathan Yang, Jordi Salvador, Joseph J. Lim, Junhyek Han, Kaiyuan Wang, Kanishka Rao, Karl Pertsch, Karol Hausman, Keegan Go, Keerthana Gopalakrishnan, Ken Goldberg, Kendra Byrne, Kenneth Oslund, Kento Kawaharazuka, Kevin Black, Kevin Lin, Kevin Zhang, Kiana Ehsani, Kiran Lekkala, Kirsty Ellis, Krishan Rana, Krishnan Srinivasan, Kuan Fang, Kunal Pratap Singh, Kuo-Hao Zeng, Kyle Hatch, Kyle Hsu, Laurent Itti, Lawrence Yunliang Chen, Lerrel Pinto, Li Fei-Fei, Liam Tan, Linxi Jim Fan, Lionel Ott, Lisa Lee, Luca Weihs, Magnum Chen, Marion Lepert, Marius Memmel, Masayoshi Tomizuka, Masha Itkina, Mateo Guaman Castro, Max Spero, Maximilian Du, Michael Ahn, Michael C. Yip, Mingtong Zhang, Mingyu Ding, Minho Heo, Mohan Kumar Srirama, Mohit Sharma, Moo Jin Kim, Naoaki Kanazawa, Nicklas Hansen, Nicolas Heess, Nikhil J. Joshi, Niko Sünderhauf, Ning Liu, Norman Di Palo, Nur Muhammad (Mahi) Shafiullah, Oier Mees, Oliver Kroemer, Osbert Bastani, Pannag R. Sanketi, Patrick Tree Miller, Patrick Yin, Paul Wohlhart, Peng Xu, Peter David Fagan, Peter Mitrano, Pierre Sermanet, Pieter Abbeel, Priya Sundaresan, Qiuyu Chen, Quan Vuong, Rafael Rafailov, Ran Tian, Ria Doshi, Roberto Martín-Martín, Rohan Baijal, Rosario Scalise, Rose Hendrix, Roy Lin, Runjia Qian, Ruohan Zhang, Russell Mendonca, Rutav Shah, Ryan Hoque, Ryan Julian, Samuel Bustamante, Sean Kirmani, Sergey Levine, Shan Lin, Sherry Moore, Shikhar Bahl, Shivin Dass, Shubham D. Sonawani, Shuran Song, Sichun Xu, Siddhant Haldar, Siddharth Karamcheti, Simeon Adebola, Simon Guist, Soroush Nasiriany, Stefan Schaal, Stefan Welker, Stephen Tian, Subramanian Ramamoorthy, Sudeep Dasari, Suneel Belkhale, Sungjae Park, Suraj Nair, Suvir Mirchandani, Takayuki Osa, Tanmay Gupta, Tatsuya Harada, Tatsuya Matsushima, Ted Xiao, Thomas Kollar, Tianhe Yu, Tianli Ding, Todor Davchev, Tony Z. Zhao, Travis Armstrong, Trevor Darrell, Trinity Chung, Vidhi Jain, Vincent Vanhoucke, Wei Zhan, Wenxuan Zhou, Wolfram Burgard, Xi Chen, Xiaolong Wang, Xinghao Zhu, Xinyang Geng, Xiyuan Liu, Liangwei Xu, Xuanlin Li, Yao Lu, Yecheng Jason Ma, Yejin Kim, Yevgen Chebotar, Yifan Zhou, Yifeng Zhu, Yilin Wu, Ying Xu, Yixuan Wang, Yonatan Bisk, Yoonyoung Cho, Youngwoon Lee, Yuchen Cui, Yue Cao, Yueh-Hua Wu, Yujin Tang, Yuke Zhu, Yunchu Zhang, Yunfan Jiang, Yunshuang Li, Yunzhu Li, Yusuke Iwasawa, Yutaka Matsuo, Zehan Ma, Zhuo Xu, Zichen Jeff Cui, Zichen Zhang, Zipeng Lin:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration. ICRA 2024: 6892-6903 - [c114]Jensen Gao, Bidipta Sarkar, Fei Xia, Ted Xiao, Jiajun Wu, Brian Ichter, Anirudha Majumdar, Dorsa Sadigh:
Physically Grounded Vision-Language Models for Robotic Manipulation. ICRA 2024: 12462-12469 - [c113]Lihan Zha, Yuchen Cui, Li-Heng Lin, Minae Kwon, Montserrat Gonzalez Arenas, Andy Zeng, Fei Xia, Dorsa Sadigh:
Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections. ICRA 2024: 15172-15179 - [i135]Boyuan Chen, Zhuo Xu, Sean Kirmani, Brian Ichter, Danny Driess, Pete Florence, Dorsa Sadigh, Leonidas J. Guibas, Fei Xia:
SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities. CoRR abs/2401.12168 (2024) - [i134]Michael Ahn, Debidatta Dwibedi, Chelsea Finn, Montse Gonzalez Arenas, Keerthana Gopalakrishnan, Karol Hausman, Brian Ichter, Alex Irpan, Nikhil J. Joshi, Ryan Julian, Sean Kirmani, Isabel Leal, Tsang-Wei Edward Lee, Sergey Levine, Yao Lu, Sharath Maddineni, Kanishka Rao, Dorsa Sadigh, Pannag Sanketi, Pierre Sermanet, Quan Vuong, Stefan Welker, Fei Xia, Ted Xiao, Peng Xu, Steve Xu, Zhuo Xu:
AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents. CoRR abs/2401.12963 (2024) - [i133]Karthik Mahadevan, Jonathan Chien, Noah Brown, Zhuo Xu, Carolina Parada, Fei Xia, Andy Zeng, Leila Takayama, Dorsa Sadigh:
Generative Expressive Robot Behaviors using Large Language Models. CoRR abs/2401.14673 (2024) - [i132]Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, Dorsa Sadigh:
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models. CoRR abs/2402.07865 (2024) - [i131]Jacky Liang, Fei Xia, Wenhao Yu, Andy Zeng, Montserrat Gonzalez Arenas, Maria Attarian, Maria Bauzá, Matthew Bennice, Alex Bewley, Adil Dostmohamed, Chuyuan Kelly Fu, Nimrod Gileadi, Marissa Giustina, Keerthana Gopalakrishnan, Leonard Hasenclever, Jan Humplik, Jasmine Hsu, Nikhil J. Joshi, Ben Jyenis, J. Chase Kew, Sean Kirmani, Tsang-Wei Edward Lee, Kuang-Huei Lee, Assaf Hurwitz Michaely, Joss Moore, Ken Oslund, Dushyant Rao, Allen Z. Ren, Baruch Tabanpour, Quan Vuong, Ayzaan Wahid, Ted Xiao, Ying Xu, Vincent Zhuang, Peng Xu, Erik Frey, Ken Caluwaerts, Tingnan Zhang, Brian Ichter, Jonathan Tompson, Leila Takayama, Vincent Vanhoucke, Izhak Shafran, Maja J. Mataric, Dorsa Sadigh, Nicolas Heess, Kanishka Rao, Nik Stewart, Jie Tan, Carolina Parada:
Learning to Learn Faster from Human Feedback with Language Model Predictive Control. CoRR abs/2402.11450 (2024) - [i130]Erdem Biyik, Nima Anari, Dorsa Sadigh:
Batch Active Learning of Reward Functions from Human Preferences. CoRR abs/2402.15757 (2024) - [i129]Jonathan Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah, Quan Vuong, Chelsea Finn, Dorsa Sadigh, Sergey Levine:
Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation. CoRR abs/2402.19432 (2024) - [i128]Suneel Belkhale, Tianli Ding, Ted Xiao, Pierre Sermanet, Quon Vuong, Jonathan Tompson, Yevgen Chebotar, Debidatta Dwibedi, Dorsa Sadigh:
RT-H: Action Hierarchies Using Language. CoRR abs/2403.01823 (2024) - [i127]Priya Sundaresan, Quan Vuong, Jiayuan Gu, Peng Xu, Ted Xiao, Sean Kirmani, Tianhe Yu, Michael Stark, Ajinkya Jain, Karol Hausman, Dorsa Sadigh, Jeannette Bohg, Stefan Schaal:
RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches. CoRR abs/2403.02709 (2024) - [i126]Jensen Gao, Annie Xie, Ted Xiao, Chelsea Finn, Dorsa Sadigh:
Efficient Data Collection for Robotic Manipulation via Compositional Generalization. CoRR abs/2403.05110 (2024) - [i125]Allen Z. Ren, Jaden Clark, Anushri Dixit, Masha Itkina, Anirudha Majumdar, Dorsa Sadigh:
Explore until Confident: Efficient Exploration for Embodied Question Answering. CoRR abs/2403.15941 (2024) - [i124]Megha Srivastava, Cédric Colas, Dorsa Sadigh, Jacob Andreas:
Policy Learning with a Language Bottleneck. CoRR abs/2405.04118 (2024) - [i123]Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch, Kevin Black, Oier Mees, Sudeep Dasari, Joey Hejna, Tobias Kreiman, Charles Xu, Jianlan Luo, You Liang Tan, Lawrence Yunliang Chen, Pannag Sanketi, Quan Vuong, Ted Xiao, Dorsa Sadigh, Chelsea Finn, Sergey Levine:
Octo: An Open-Source Generalist Robot Policy. CoRR abs/2405.12213 (2024) - [i122]Michael Ahn, Montserrat Gonzalez Arenas, Matthew Bennice, Noah Brown, Christine Chan, Byron David, Anthony G. Francis, Gavin Gonzalez, Rainer Hessmer, Tomas Jackson, Nikhil J. Joshi, Daniel Lam, Tsang-Wei Edward Lee, Alex Luong, Sharath Maddineni, Harsh Patel, Jodilyn Peralta, Jornell Quiambao, Diego Reyes, Rosario Jauregui Ruano, Dorsa Sadigh, Pannag Sanketi, Leila Takayama, Pavel Vodenski, Fei Xia:
VADER: Visual Affordance Detection and Error Recovery for Multi Robot Human Collaboration. CoRR abs/2405.16021 (2024) - [i121]Moo Jin Kim, Karl Pertsch, Siddharth Karamcheti, Ted Xiao, Ashwin Balakrishna, Suraj Nair, Rafael Rafailov, Ethan Paul Foster, Grace Lam, Pannag Sanketi, Quan Vuong, Thomas Kollar, Benjamin Burchfiel, Russ Tedrake, Dorsa Sadigh, Sergey Levine, Percy Liang, Chelsea Finn:
OpenVLA: An Open-Source Vision-Language-Action Model. CoRR abs/2406.09246 (2024) - [i120]Rajat Kumar Jenamani, Priya Sundaresan, Maram Sakr, Tapomayukh Bhattacharjee, Dorsa Sadigh:
FLAIR: Feeding via Long-horizon AcquIsition of Realistic dishes. CoRR abs/2407.07561 (2024) - [i119]Joey Hejna, Chethan Bhateja, Yichen Jian, Karl Pertsch, Dorsa Sadigh:
Re-Mix: Optimizing Data Mixtures for Large Scale Imitation Learning. CoRR abs/2408.14037 (2024) - [i118]Li-Heng Lin, Yuchen Cui, Amber Xie, Tianyu Hua, Dorsa Sadigh:
FlowRetrieval: Flow-Guided Data Retrieval for Few-Shot Imitation Learning. CoRR abs/2408.16944 (2024) - [i117]Minyoung Hwang, Joey Hejna, Dorsa Sadigh, Yonatan Bisk:
MotIF: Motion Instruction Fine-tuning. CoRR abs/2409.10683 (2024) - [i116]Homanga Bharadhwaj, Debidatta Dwibedi, Abhinav Gupta, Shubham Tulsiani, Carl Doersch, Ted Xiao, Dhruv Shah, Fei Xia, Dorsa Sadigh, Sean Kirmani:
Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation. CoRR abs/2409.16283 (2024) - 2023
- [j15]Tim Salzmann, Hao-Tien Lewis Chiang, Markus Ryll, Dorsa Sadigh, Carolina Parada, Alex Bewley:
Robots That Can See: Leveraging Human Pose for Trajectory Prediction. IEEE Robotics Autom. Lett. 8(11): 7090-7097 (2023) - [j14]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. 2023 (2023) - [c112]Dorsa Sadigh:
Interactive Learning and Control in the Era of Large Models. CDC 2023: 2992 - [c111]Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montserrat Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, Brian Ichter, Ted Xiao, Peng Xu, Andy Zeng, Tingnan Zhang, Nicolas Heess, Dorsa Sadigh, Jie Tan, Yuval Tassa, Fei Xia:
Language to Rewards for Robotic Skill Synthesis. CoRL 2023: 374-404 - [c110]Jennifer Grannen, Yilin Wu, Brandon Vu, Dorsa Sadigh:
Stabilize to Act: Learning to Coordinate for Bimanual Manipulation. CoRL 2023: 563-576 - [c109]Allen Z. Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu, Dorsa Sadigh, Andy Zeng, Anirudha Majumdar:
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners. CoRL 2023: 661-682 - [c108]Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh, Jeannette Bohg:
KITE: Keypoint-Conditioned Policies for Semantic Manipulation. CoRL 2023: 1006-1021 - [c107]Priya Sundaresan, Jiajun Wu, Dorsa Sadigh:
Learning Sequential Acquisition Policies for Robot-Assisted Feeding. CoRL 2023: 1282-1299 - [c106]Suneel Belkhale, Yuchen Cui, Dorsa Sadigh:
HYDRA: Hybrid Robot Actions for Imitation Learning. CoRL 2023: 2113-2133 - [c105]Suvir Mirchandani, Fei Xia, Pete Florence, Brian Ichter, Danny Driess, Montserrat Gonzalez Arenas, Kanishka Rao, Dorsa Sadigh, Andy Zeng:
Large Language Models as General Pattern Machines. CoRL 2023: 2498-2518 - [c104]Jonathan Heewon Yang, Dorsa Sadigh, Chelsea Finn:
Polybot: Training One Policy Across Robots While Embracing Variability. CoRL 2023: 2955-2974 - [c103]Li-Heng Lin, Yuchen Cui, Yilun Hao, Fei Xia, Dorsa Sadigh:
Gesture-Informed Robot Assistance via Foundation Models. CoRL 2023: 3061-3082 - [c102]Yuchen Cui, Siddharth Karamcheti, Raj Palleti, Nidhya Shivakumar, Percy Liang, Dorsa Sadigh:
No, to the Right: Online Language Corrections for Robotic Manipulation via Shared Autonomy. HRI 2023: 93-101 - [c101]Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh:
Reward Design with Language Models. ICLR 2023 - [c100]Joey Hejna, Jensen Gao, Dorsa Sadigh:
Distance Weighted Supervised Learning for Offline Interaction Data. ICML 2023: 12882-12906 - [c99]Hengyuan Hu, Dorsa Sadigh:
Language Instructed Reinforcement Learning for Human-AI Coordination. ICML 2023: 13584-13598 - [c98]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Long Horizon Temperature Scaling. ICML 2023: 31422-31434 - [c97]Megha Srivastava, Noah D. Goodman, Dorsa Sadigh:
Generating Language Corrections for Teaching Physical Control Tasks. ICML 2023: 32561-32574 - [c96]Mengxi Li, Rika Antonova, Dorsa Sadigh, Jeannette Bohg:
Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation. ICRA 2023: 1859-1865 - [c95]Vivek Myers, Erdem Biyik, Dorsa Sadigh:
Active Reward Learning from Online Preferences. ICRA 2023: 7511-7518 - [c94]Lorenzo Shaikewitz, Yilin Wu, Suneel Belkhale, Jennifer Grannen, Priya Sundaresan, Dorsa Sadigh:
In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing. ICRA 2023: 9885-9895 - [c93]Yilun Hao, Ruinan Wang, Zhangjie Cao, Zihan Wang, Yuchen Cui, Dorsa Sadigh:
Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations. IROS 2023: 1-7 - [c92]Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett:
Soy: An Efficient MILP Solver for Piecewise-Affine Systems. IROS 2023: 6281-6288 - [c91]Suneel Belkhale, Yuchen Cui, Dorsa Sadigh:
Data Quality in Imitation Learning. NeurIPS 2023 - [c90]Joey Hejna, Dorsa Sadigh:
Inverse Preference Learning: Preference-based RL without a Reward Function. NeurIPS 2023 - [c89]Bidipta Sarkar, Andy Shih, Dorsa Sadigh:
Diverse Conventions for Human-AI Collaboration. NeurIPS 2023 - [c88]Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari:
Parallel Sampling of Diffusion Models. NeurIPS 2023 - [c87]Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. NeurIPS 2023 - [c86]Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn:
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets. Robotics: Science and Systems 2023 - [c85]Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang:
Language-Driven Representation Learning for Robotics. Robotics: Science and Systems 2023 - [e1]Steven M. LaValle, Jason M. O'Kane, Michael W. Otte, Dorsa Sadigh, Pratap Tokekar:
Algorithmic Foundations of Robotics XV - Proceedings of the Fifteenth Workshop on the Algorithmic Foundations of Robotics, WAFR 2022, College Park, MD, USA, 22-24 June, 2022. Springer Proceedings in Advanced Robotics 25, Springer 2023, ISBN 978-3-031-21089-1 [contents] - [i115]Yuchen Cui, Siddharth Karamcheti, Raj Palleti, Nidhya Shivakumar, Percy Liang, Dorsa Sadigh:
"No, to the Right" - Online Language Corrections for Robotic Manipulation via Shared Autonomy. CoRR abs/2301.02555 (2023) - [i114]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Long Horizon Temperature Scaling. CoRR abs/2302.03686 (2023) - [i113]Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang:
Language-Driven Representation Learning for Robotics. CoRR abs/2302.12766 (2023) - [i112]Vivek Myers, Erdem Biyik, Dorsa Sadigh:
Active Reward Learning from Online Preferences. CoRR abs/2302.13507 (2023) - [i111]Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh:
Reward Design with Language Models. CoRR abs/2303.00001 (2023) - [i110]Haoze Wu, Min Wu, Dorsa Sadigh, Clark W. Barrett:
Soy: An Efficient MILP Solver for Piecewise-Affine Systems. CoRR abs/2303.13697 (2023) - [i109]Hengyuan Hu, Dorsa Sadigh:
Language Instructed Reinforcement Learning for Human-AI Coordination. CoRR abs/2304.07297 (2023) - [i108]Maximilian Du, Suraj Nair, Dorsa Sadigh, Chelsea Finn:
Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets. CoRR abs/2304.08742 (2023) - [i107]Joey Hejna, Jensen Gao, Dorsa Sadigh:
Distance Weighted Supervised Learning for Offline Interaction Data. CoRR abs/2304.13774 (2023) - [i106]Joey Hejna, Dorsa Sadigh:
Inverse Preference Learning: Preference-based RL without a Reward Function. CoRR abs/2305.15363 (2023) - [i105]Andy Shih, Suneel Belkhale, Stefano Ermon, Dorsa Sadigh, Nima Anari:
Parallel Sampling of Diffusion Models. CoRR abs/2305.16317 (2023) - [i104]Kanishk Gandhi, Dorsa Sadigh, Noah D. Goodman:
Strategic Reasoning with Language Models. CoRR abs/2305.19165 (2023) - [i103]Suneel Belkhale, Yuchen Cui, Dorsa Sadigh:
Data Quality in Imitation Learning. CoRR abs/2306.02437 (2023) - [i102]Megha Srivastava, Noah D. Goodman, Dorsa Sadigh:
Generating Language Corrections for Teaching Physical Control Tasks. CoRR abs/2306.07012 (2023) - [i101]Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montse Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, Brian Ichter, Ted Xiao, Peng Xu, Andy Zeng, Tingnan Zhang, Nicolas Heess, Dorsa Sadigh, Jie Tan, Yuval Tassa, Fei Xia:
Language to Rewards for Robotic Skill Synthesis. CoRR abs/2306.08647 (2023) - [i100]Minae Kwon, Hengyuan Hu, Vivek Myers, Siddharth Karamcheti, Anca D. Dragan, Dorsa Sadigh:
Toward Grounded Social Reasoning. CoRR abs/2306.08651 (2023) - [i99]Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh, Jeannette Bohg:
KITE: Keypoint-Conditioned Policies for Semantic Manipulation. CoRR abs/2306.16605 (2023) - [i98]Suneel Belkhale, Yuchen Cui, Dorsa Sadigh:
HYDRA: Hybrid Robot Actions for Imitation Learning. CoRR abs/2306.17237 (2023) - [i97]Allen Z. Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, Zhenjia Xu, Dorsa Sadigh, Andy Zeng, Anirudha Majumdar:
Robots That Ask For Help: Uncertainty Alignment for Large Language Model Planners. CoRR abs/2307.01928 (2023) - [i96]Jonathan Heewon Yang, Dorsa Sadigh, Chelsea Finn:
Polybot: Training One Policy Across Robots While Embracing Variability. CoRR abs/2307.03719 (2023) - [i95]Suvir Mirchandani, Fei Xia, Pete Florence, Brian Ichter, Danny Driess, Montserrat Gonzalez Arenas, Kanishka Rao, Dorsa Sadigh, Andy Zeng:
Large Language Models as General Pattern Machines. CoRR abs/2307.04721 (2023) - [i94]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. CoRR abs/2307.15217 (2023) - [i93]Jennifer Grannen, Yilin Wu, Brandon Vu, Dorsa Sadigh:
Stabilize to Act: Learning to Coordinate for Bimanual Manipulation. CoRR abs/2309.01087 (2023) - [i92]Jensen Gao, Bidipta Sarkar, Fei Xia, Ted Xiao, Jiajun Wu, Brian Ichter, Anirudha Majumdar, Dorsa Sadigh:
Physically Grounded Vision-Language Models for Robotic Manipulation. CoRR abs/2309.02561 (2023) - [i91]Li-Heng Lin, Yuchen Cui, Yilun Hao, Fei Xia, Dorsa Sadigh:
Gesture-Informed Robot Assistance via Foundation Models. CoRR abs/2309.02721 (2023) - [i90]Priya Sundaresan, Jiajun Wu, Dorsa Sadigh:
Learning Sequential Acquisition Policies for Robot-Assisted Feeding. CoRR abs/2309.05197 (2023) - [i89]Tim Salzmann, Lewis Chiang, Markus Ryll, Dorsa Sadigh, Carolina Parada, Alex Bewley:
Robots That Can See: Leveraging Human Pose for Trajectory Prediction. CoRR abs/2309.17209 (2023) - [i88]Sumedh A. Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. CoRR abs/2310.07899 (2023) - [i87]Open X.-Embodiment Collaboration, Abhishek Padalkar, Acorn Pooley, Ajinkya Jain, Alex Bewley, Alexander Herzog, Alex Irpan, Alexander Khazatsky, Anant Raj, Anikait Singh, Anthony Brohan, Antonin Raffin, Ayzaan Wahid, Ben Burgess-Limerick, Beomjoon Kim, Bernhard Schölkopf, Brian Ichter, Cewu Lu, Charles Xu, Chelsea Finn, Chenfeng Xu, Cheng Chi, Chenguang Huang, Christine Chan, Chuer Pan, Chuyuan Fu, Coline Devin, Danny Driess, Deepak Pathak, Dhruv Shah, Dieter Büchler, Dmitry Kalashnikov, Dorsa Sadigh, Edward Johns, Federico Ceola, Fei Xia, Freek Stulp, Gaoyue Zhou, Gaurav S. Sukhatme, Gautam Salhotra, Ge Yan, Giulio Schiavi, Gregory Kahn, Hao Su, Haoshu Fang, Haochen Shi, Heni Ben Amor, Henrik I. Christensen, Hiroki Furuta, Homer Walke, Hongjie Fang, Igor Mordatch, Ilija Radosavovic, et al.:
Open X-Embodiment: Robotic Learning Datasets and RT-X Models. CoRR abs/2310.08864 (2023) - [i86]Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh:
Contrastive Preference Learning: Learning from Human Feedback without RL. CoRR abs/2310.13639 (2023) - [i85]Bidipta Sarkar, Andy Shih, Dorsa Sadigh:
Diverse Conventions for Human-AI Collaboration. CoRR abs/2310.15414 (2023) - [i84]Hengyuan Hu, Suvir Mirchandani, Dorsa Sadigh:
Imitation Bootstrapped Reinforcement Learning. CoRR abs/2311.02198 (2023) - [i83]Lihan Zha, Yuchen Cui, Li-Heng Lin, Minae Kwon, Montserrat Gonzalez Arenas, Andy Zeng, Fei Xia, Dorsa Sadigh:
Distilling and Retrieving Generalizable Knowledge for Robot Manipulation via Language Corrections. CoRR abs/2311.10678 (2023) - [i82]Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter:
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. CoRR abs/2312.04474 (2023) - 2022
- [j13]Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh:
Learning latent actions to control assistive robots. Auton. Robots 46(1): 115-147 (2022) - [j12]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic multi-robot task allocation under uncertainty and temporal constraints. Auton. Robots 46(1): 231-247 (2022) - [j11]Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry:
Toward verified artificial intelligence. Commun. ACM 65(7): 46-55 (2022) - [j10]Erdem Biyik, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh:
Learning reward functions from diverse sources of human feedback: Optimally integrating demonstrations and preferences. Int. J. Robotics Res. 41(1): 45-67 (2022) - [j9]Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah:
Social Coordination and Altruism in Autonomous Driving. IEEE Trans. Intell. Transp. Syst. 23(12): 24791-24804 (2022) - [c84]Erdem Biyik, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh:
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams. AAAI 2022: 9296-9303 - [c83]Bidipta Sarkar, Aditi Talati, Andy Shih, Dorsa Sadigh:
PantheonRL: A MARL Library for Dynamic Training Interactions. AAAI 2022: 13221-13223 - [c82]Erik Brockbank, Haoliang Wang, Justin Yang, Suvir Mirchandani, Erdem Biyik, Dorsa Sadigh, Judith E. Fan:
How do people incorporate advice from artificial agents when making physical judgments? CogSci 2022 - [c81]Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh:
Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding. CoRL 2022: 332-341 - [c80]Suneel Belkhale, Dorsa Sadigh:
PLATO: Predicting Latent Affordances Through Object-Centric Play. CoRL 2022: 1424-1434 - [c79]Jennifer Grannen, Yilin Wu, Suneel Belkhale, Dorsa Sadigh:
Learning Bimanual Scooping Policies for Food Acquisition. CoRL 2022: 1510-1519 - [c78]Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh:
Eliciting Compatible Demonstrations for Multi-Human Imitation Learning. CoRL 2022: 1981-1991 - [c77]Donald Joseph Hejna III, Dorsa Sadigh:
Few-Shot Preference Learning for Human-in-the-Loop RL. CoRL 2022: 2014-2025 - [c76]Andy Shih, Stefano Ermon, Dorsa Sadigh:
Conditional Imitation Learning for Multi-Agent Games. HRI 2022: 166-175 - [c75]Erdem Biyik, Aditi Talati, Dorsa Sadigh:
APReL: A Library for Active Preference-based Reward Learning Algorithms. HRI 2022: 613-617 - [c74]Mark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani:
Imitation Learning by Estimating Expertise of Demonstrators. ICML 2022: 1732-1748 - [c73]Zhangjie Cao, Zihan Wang, Dorsa Sadigh:
Learning from Imperfect Demonstrations via Adversarial Confidence Transfer. ICRA 2022: 441-447 - [c72]Zihan Wang, Zhangjie Cao, Yilun Hao, Dorsa Sadigh:
Weakly Supervised Correspondence Learning. ICRA 2022: 469-476 - [c71]Suneel Belkhale, Ethan K. Gordon, Yuxiao Chen, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Dorsa Sadigh:
Balancing Efficiency and Comfort in Robot-Assisted Bite Transfer. ICRA 2022: 4757-4763 - [c70]Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh:
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction. ICRA 2022: 10723-10730 - [c69]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Training and Inference on Any-Order Autoregressive Models the Right Way. NeurIPS 2022 - [c68]Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh:
Assistive Teaching of Motor Control Tasks to Humans. NeurIPS 2022 - [i81]Andy Shih, Stefano Ermon, Dorsa Sadigh:
Conditional Imitation Learning for Multi-Agent Games. CoRR abs/2201.01448 (2022) - [i80]Mark Beliaev, Andy Shih, Stefano Ermon, Dorsa Sadigh, Ramtin Pedarsani:
Imitation Learning by Estimating Expertise of Demonstrators. CoRR abs/2202.01288 (2022) - [i79]Zhangjie Cao, Zihan Wang, Dorsa Sadigh:
Learning from Imperfect Demonstrations via Adversarial Confidence Transfer. CoRR abs/2202.02967 (2022) - [i78]Zihan Wang, Zhangjie Cao, Yilun Hao, Dorsa Sadigh:
Weakly Supervised Correspondence Learning. CoRR abs/2203.00904 (2022) - [i77]Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh:
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction. CoRR abs/2203.04421 (2022) - [i76]Suneel Belkhale, Dorsa Sadigh:
PLATO: Predicting Latent Affordances Through Object-Centric Play. CoRR abs/2203.05630 (2022) - [i75]Erik Brockbank, Haoliang Wang, Justin Yang, Suvir Mirchandani, Erdem Biyik, Dorsa Sadigh, Judith E. Fan:
How do people incorporate advice from artificial agents when making physical judgments? CoRR abs/2205.11613 (2022) - [i74]Andy Shih, Dorsa Sadigh, Stefano Ermon:
Training and Inference on Any-Order Autoregressive Models the Right Way. CoRR abs/2205.13554 (2022) - [i73]Yilun Hao, Ruinan Wang, Zhangjie Cao, Zihan Wang, Yuchen Cui, Dorsa Sadigh:
Masked Imitation Learning: Discovering Environment-Invariant Modalities in Multimodal Demonstrations. CoRR abs/2209.07682 (2022) - [i72]Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao, Dorsa Sadigh:
Eliciting Compatible Demonstrations for Multi-Human Imitation Learning. CoRR abs/2210.08073 (2022) - [i71]Mengxi Li, Rika Antonova, Dorsa Sadigh, Jeannette Bohg:
Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation. CoRR abs/2211.02201 (2022) - [i70]Lorenzo Shaikewitz, Yilin Wu, Suneel Belkhale, Jennifer Grannen, Priya Sundaresan, Dorsa Sadigh:
In-Mouth Robotic Bite Transfer with Visual and Haptic Sensing. CoRR abs/2211.12705 (2022) - [i69]Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh:
Assistive Teaching of Motor Control Tasks to Humans. CoRR abs/2211.14003 (2022) - [i68]Priya Sundaresan, Suneel Belkhale, Dorsa Sadigh:
Learning Visuo-Haptic Skewering Strategies for Robot-Assisted Feeding. CoRR abs/2211.14648 (2022) - [i67]Jennifer Grannen, Yilin Wu, Suneel Belkhale, Dorsa Sadigh:
Learning Bimanual Scooping Policies for Food Acquisition. CoRR abs/2211.14652 (2022) - [i66]Joey Hejna, Dorsa Sadigh:
Few-Shot Preference Learning for Human-in-the-Loop RL. CoRR abs/2212.03363 (2022) - 2021
- [j8]Mengxi Li, Minae Kwon, Dorsa Sadigh:
Influencing leading and following in human-robot teams. Auton. Robots 45(7): 959-978 (2021) - [j7]Hadas Kress-Gazit, Kerstin Eder, Guy Hoffman, Henny Admoni, Brenna Argall, Rüdiger Ehlers, Christoffer Heckman, Nils Jansen, Ross A. Knepper, Jan Kretínský, Shelly Levy-Tzedek, Jamy Li, Todd D. Murphey, Laurel D. Riek, Dorsa Sadigh:
Formalizing and guaranteeing human-robot interaction. Commun. ACM 64(9): 78-84 (2021) - [j6]Zhangjie Cao, Minae Kwon, Dorsa Sadigh:
Transfer Reinforcement Learning Across Homotopy Classes. IEEE Robotics Autom. Lett. 6(2): 2706-2713 (2021) - [j5]Zhangjie Cao, Dorsa Sadigh:
Learning From Imperfect Demonstrations From Agents With Varying Dynamics. IEEE Robotics Autom. Lett. 6(3): 5231-5238 (2021) - [j4]Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Incentivizing Efficient Equilibria in Traffic Networks With Mixed Autonomy. IEEE Trans. Control. Netw. Syst. 8(4): 1717-1729 (2021) - [c67]Vivek Myers, Erdem Biyik, Nima Anari, Dorsa Sadigh:
Learning Multimodal Rewards from Rankings. CoRL 2021: 342-352 - [c66]Nils Wilde, Erdem Biyik, Dorsa Sadigh, Stephen L. Smith:
Learning Reward Functions from Scale Feedback. CoRL 2021: 353-362 - [c65]Zhangjie Cao, Yilun Hao, Mengxi Li, Dorsa Sadigh:
Learning Feasibility to Imitate Demonstrators with Different Dynamics. CoRL 2021: 363-372 - [c64]Woodrow Zhouyuan Wang, Andy Shih, Annie Xie, Dorsa Sadigh:
Influencing Towards Stable Multi-Agent Interactions. CoRL 2021: 1132-1143 - [c63]Siddharth Karamcheti, Megha Srivastava, Percy Liang, Dorsa Sadigh:
LILA: Language-Informed Latent Actions. CoRL 2021: 1379-1390 - [c62]Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman:
Open-domain clarification question generation without question examples. EMNLP (1) 2021: 563-570 - [c61]Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani:
Incentivizing routing choices for safe and efficient transportation in the face of the COVID-19 pandemic. ICCPS 2021: 187-197 - [c60]Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh:
On the Critical Role of Conventions in Adaptive Human-AI Collaboration. ICLR 2021 - [c59]Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh:
Targeted Data Acquisition for Evolving Negotiation Agents. ICML 2021: 5894-5904 - [c58]Mengxi Li, Alper Canberk, Dylan P. Losey, Dorsa Sadigh:
Learning Human Objectives from Sequences of Physical Corrections. ICRA 2021: 2877-2883 - [c57]Kejun Li, Maegan Tucker, Erdem Biyik, Ellen R. Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames:
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. ICRA 2021: 3212-3218 - [c56]Woodrow Z. Wang, Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Emergent Prosociality in Multi-Agent Games Through Gifting. IJCAI 2021: 434-442 - [c55]Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah:
Cooperative Autonomous Vehicles that Sympathize with Human Drivers. IROS 2021: 4517-4524 - [c54]Siddharth Karamcheti, Albert J. Zhai, Dylan P. Losey, Dorsa Sadigh:
Learning Visually Guided Latent Actions for Assistive Teleoperation. L4DC 2021: 1230-1241 - [c53]Andy Shih, Dorsa Sadigh, Stefano Ermon:
HyperSPNs: Compact and Expressive Probabilistic Circuits. NeurIPS 2021: 8571-8582 - [c52]Songyuan Zhang, Zhangjie Cao, Dorsa Sadigh, Yanan Sui:
Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality. NeurIPS 2021: 12340-12350 - [c51]Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh:
ELLA: Exploration through Learned Language Abstraction. NeurIPS 2021: 29529-29540 - [i65]Zhangjie Cao, Minae Kwon, Dorsa Sadigh:
Transfer Reinforcement Learning across Homotopy Classes. CoRR abs/2102.05207 (2021) - [i64]Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh:
ELLA: Exploration through Learned Language Abstraction. CoRR abs/2103.05825 (2021) - [i63]Zhangjie Cao, Dorsa Sadigh:
Learning from Imperfect Demonstrations from Agents with Varying Dynamics. CoRR abs/2103.05910 (2021) - [i62]Mengxi Li, Alper Canberk, Dylan P. Losey, Dorsa Sadigh:
Learning Human Objectives from Sequences of Physical Corrections. CoRR abs/2104.00078 (2021) - [i61]Andy Shih, Arjun Sawhney, Jovana Kondic, Stefano Ermon, Dorsa Sadigh:
On the Critical Role of Conventions in Adaptive Human-AI Collaboration. CoRR abs/2104.02871 (2021) - [i60]Siddharth Karamcheti, Albert J. Zhai, Dylan P. Losey, Dorsa Sadigh:
Learning Visually Guided Latent Actions for Assistive Teleoperation. CoRR abs/2105.00580 (2021) - [i59]Woodrow Z. Wang, Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Emergent Prosociality in Multi-Agent Games Through Gifting. CoRR abs/2105.06593 (2021) - [i58]Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy. CoRR abs/2106.04678 (2021) - [i57]Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh:
Targeted Data Acquisition for Evolving Negotiation Agents. CoRR abs/2106.07728 (2021) - [i56]Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah:
Social Coordination and Altruism in Autonomous Driving. CoRR abs/2107.00200 (2021) - [i55]Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah:
Cooperative Autonomous Vehicles that Sympathize with Human Drivers. CoRR abs/2107.00898 (2021) - [i54]Dylan P. Losey, Hong Jun Jeon, Mengxi Li, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Jeannette Bohg, Dorsa Sadigh:
Learning Latent Actions to Control Assistive Robots. CoRR abs/2107.02907 (2021) - [i53]Behrad Toghi, Rodolfo Valiente, Dorsa Sadigh, Ramtin Pedarsani, Yaser P. Fallah:
Altruistic Maneuver Planning for Cooperative Autonomous Vehicles Using Multi-agent Advantage Actor-Critic. CoRR abs/2107.05664 (2021) - [i52]Erdem Biyik, Aditi Talati, Dorsa Sadigh:
APReL: A Library for Active Preference-based Reward Learning Algorithms. CoRR abs/2108.07259 (2021) - [i51]Vivek Myers, Erdem Biyik, Nima Anari, Dorsa Sadigh:
Learning Multimodal Rewards from Rankings. CoRR abs/2109.12750 (2021) - [i50]Nils Wilde, Erdem Biyik, Dorsa Sadigh, Stephen L. Smith:
Learning Reward Functions from Scale Feedback. CoRR abs/2110.00284 (2021) - [i49]Erdem Biyik, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh:
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams. CoRR abs/2110.00751 (2021) - [i48]Woodrow Z. Wang, Andy Shih, Annie Xie, Dorsa Sadigh:
Influencing Towards Stable Multi-Agent Interactions. CoRR abs/2110.08229 (2021) - [i47]Julia White, Gabriel Poesia, Robert X. D. Hawkins, Dorsa Sadigh, Noah D. Goodman:
Open-domain clarification question generation without question examples. CoRR abs/2110.09779 (2021) - [i46]Songyuan Zhang, Zhangjie Cao, Dorsa Sadigh, Yanan Sui:
Confidence-Aware Imitation Learning from Demonstrations with Varying Optimality. CoRR abs/2110.14754 (2021) - [i45]Zhangjie Cao, Yilun Hao, Mengxi Li, Dorsa Sadigh:
Learning Feasibility to Imitate Demonstrators with Different Dynamics. CoRR abs/2110.15142 (2021) - [i44]Nicholas Roy, Ingmar Posner, Tim D. Barfoot, Philippe Beaudoin, Yoshua Bengio, Jeannette Bohg, Oliver Brock, Isabelle Depatie, Dieter Fox, Daniel E. Koditschek, Tomás Lozano-Pérez, Vikash Mansinghka, Christopher J. Pal, Blake A. Richards, Dorsa Sadigh, Stefan Schaal, Gaurav S. Sukhatme, Denis Thérien, Marc Toussaint, Michiel van de Panne:
From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence. CoRR abs/2110.15245 (2021) - [i43]Siddharth Karamcheti, Megha Srivastava, Percy Liang, Dorsa Sadigh:
LILA: Language-Informed Latent Actions. CoRR abs/2111.03205 (2021) - [i42]Suneel Belkhale, Ethan K. Gordon, Yuxiao Chen, Siddhartha S. Srinivasa, Tapomayukh Bhattacharjee, Dorsa Sadigh:
Balancing Efficiency and Comfort in Robot-Assisted Bite Transfer. CoRR abs/2111.11401 (2021) - [i41]Andy Shih, Dorsa Sadigh, Stefano Ermon:
HyperSPNs: Compact and Expressive Probabilistic Circuits. CoRR abs/2112.00914 (2021) - [i40]Bidipta Sarkar, Aditi Talati, Andy Shih, Dorsa Sadigh:
PantheonRL: A MARL Library for Dynamic Training Interactions. CoRR abs/2112.07013 (2021) - 2020
- [j3]Yuhang Che, Allison M. Okamura, Dorsa Sadigh:
Efficient and Trustworthy Social Navigation via Explicit and Implicit Robot-Human Communication. IEEE Trans. Robotics 36(3): 692-707 (2020) - [c50]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Exchangeable Input Representations for Reinforcement Learning. ACC 2020: 3971-3976 - [c49]Robert X. D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman:
Continual Adaptation for Efficient Machine Communication. CoNLL 2020: 408-419 - [c48]Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh:
Learning Latent Representations to Influence Multi-Agent Interaction. CoRL 2020: 575-588 - [c47]Kawin Ethayarajh, Dorsa Sadigh:
BLEU Neighbors: A Reference-less Approach to Automatic Evaluation. Eval4NLP 2020: 40-50 - [c46]Minae Kwon, Erdem Biyik, Aditi Talati, Karan Bhasin, Dylan P. Losey, Dorsa Sadigh:
When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans. HRI 2020: 43-52 - [c45]Dylan P. Losey, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Dorsa Sadigh:
Controlling Assistive Robots with Learned Latent Actions. ICRA 2020: 378-384 - [c44]Zheqing Zhu, Erdem Biyik, Dorsa Sadigh:
Multi-Agent Safe Planning with Gaussian Processes. IROS 2020: 6260-6267 - [c43]Mengxi Li, Dylan P. Losey, Jeannette Bohg, Dorsa Sadigh:
Learning User-Preferred Mappings for Intuitive Robot Control. IROS 2020: 10960-10967 - [c42]Malayandi Palan, Shane T. Barratt, Alex McCauley, Dorsa Sadigh, Vikas Sindhwani, Stephen P. Boyd:
Fitting a Linear Control Policy to Demonstrations with a Kalman Constraint. L4DC 2020: 374-383 - [c41]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. Robotics: Science and Systems 2020 - [c40]Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh:
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving. Robotics: Science and Systems 2020 - [c39]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. Robotics: Science and Systems 2020 - [c38]Hong Jun Jeon, Dylan P. Losey, Dorsa Sadigh:
Shared Autonomy with Learned Latent Actions. Robotics: Science and Systems 2020 - [i39]Minae Kwon, Erdem Biyik, Aditi Talati, Karan Bhasin, Dylan P. Losey, Dorsa Sadigh:
When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans. CoRR abs/2001.04377 (2020) - [i38]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Exchangeable Input Representations for Reinforcement Learning. CoRR abs/2003.09022 (2020) - [i37]Kawin Ethayarajh, Dorsa Sadigh:
BLEU Neighbors: A Reference-less Approach to Automatic Evaluation. CoRR abs/2004.12726 (2020) - [i36]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. CoRR abs/2005.02575 (2020) - [i35]Hong Jun Jeon, Dylan P. Losey, Dorsa Sadigh:
Shared Autonomy with Learned Latent Actions. CoRR abs/2005.03210 (2020) - [i34]Shushman Choudhury, Jayesh K. Gupta, Mykel J. Kochenderfer, Dorsa Sadigh, Jeannette Bohg:
Dynamic Multi-Robot Task Allocation under Uncertainty and Temporal Constraints. CoRR abs/2005.13109 (2020) - [i33]Erdem Biyik, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh:
Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences. CoRR abs/2006.14091 (2020) - [i32]Hadas Kress-Gazit, Kerstin Eder, Guy Hoffman, Henny Admoni, Brenna Argall, Rüdiger Ehlers, Christoffer Heckman, Nils Jansen, Ross A. Knepper, Jan Kretínský, Shelly Levy-Tzedek, Jamy Li, Todd D. Murphey, Laurel D. Riek, Dorsa Sadigh:
Formalizing and Guaranteeing* Human-Robot Interaction. CoRR abs/2006.16732 (2020) - [i31]Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh:
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving. CoRR abs/2007.00178 (2020) - [i30]Mengxi Li, Dylan P. Losey, Jeannette Bohg, Dorsa Sadigh:
Learning User-Preferred Mappings for Intuitive Robot Control. CoRR abs/2007.11627 (2020) - [i29]Zheqing Zhu, Erdem Biyik, Dorsa Sadigh:
Multi-Agent Safe Planning with Gaussian Processes. CoRR abs/2008.04452 (2020) - [i28]Siddharth Karamcheti, Dorsa Sadigh, Percy Liang:
Learning Adaptive Language Interfaces through Decomposition. CoRR abs/2010.05190 (2020) - [i27]Kejun Li, Maegan Tucker, Erdem Biyik, Ellen R. Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames:
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. CoRR abs/2011.04812 (2020) - [i26]Annie Xie, Dylan P. Losey, Ryan Tolsma, Chelsea Finn, Dorsa Sadigh:
Learning Latent Representations to Influence Multi-Agent Interaction. CoRR abs/2011.06619 (2020) - [i25]Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani:
Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic. CoRR abs/2012.15749 (2020)
2010 – 2019
- 2019
- [c37]Erdem Biyik, Jonathan Margoliash, Shahrouz Ryan Alimo, Dorsa Sadigh:
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models. ACC 2019: 1792-1799 - [c36]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Object Exchangability in Reinforcement Learning. AAMAS 2019: 2126-2128 - [c35]Erdem Biyik, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani:
The Green Choice: Learning and Influencing Human Decisions on Shared Roads. CDC 2019: 347-354 - [c34]Dylan P. Losey, Mengxi Li, Jeannette Bohg, Dorsa Sadigh:
Learning from My Partner's Actions: Roles in Decentralized Robot Teams. CoRL 2019: 752-765 - [c33]Erdem Biyik, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh:
Asking Easy Questions: A User-Friendly Approach to Active Reward Learning. CoRL 2019: 1177-1190 - [c32]Elis Stefansson, Jaime F. Fisac, Dorsa Sadigh, S. Shankar Sastry, Karl Henrik Johansson:
Human-robot interaction for truck platooning using hierarchical dynamic games. ECC 2019: 3165-3172 - [c31]Dorsa Sadigh:
Safe and Interactive Autonomy: A Journey Starting from Formal Methods (Keynote). FMCAD 2019: 1 - [c30]Ashwini Pokle, Roberto Martín-Martín, Patrick Goebel, Vincent Chow, Hans M. Ewald, Junwei Yang, Zhenkai Wang, Amir Sadeghian, Dorsa Sadigh, Silvio Savarese, Marynel Vázquez:
Deep Local Trajectory Replanning and Control for Robot Navigation. ICRA 2019: 5815-5822 - [c29]Jaime F. Fisac, Eli Bronstein, Elis Stefansson, Dorsa Sadigh, S. Shankar Sastry, Anca D. Dragan:
Hierarchical Game-Theoretic Planning for Autonomous Vehicles. ICRA 2019: 9590-9596 - [c28]Chandrayee Basu, Erdem Biyik, Zhixun He, Mukesh Singhal, Dorsa Sadigh:
Active Learning of Reward Dynamics from Hierarchical Queries. IROS 2019: 120-127 - [c27]Dylan P. Losey, Dorsa Sadigh:
Robots that Take Advantage of Human Trust. IROS 2019: 7001-7008 - [c26]Minae Kwon, Mengxi Li, Alexandre Bucquet, Dorsa Sadigh:
Influencing Leading and Following in Human-Robot Teams. Robotics: Science and Systems 2019 - [c25]Malayandi Palan, Gleb Shevchuk, Nicholas Charles Landolfi, Dorsa Sadigh:
Learning Reward Functions by Integrating Human Demonstrations and Preferences. Robotics: Science and Systems 2019 - [c24]Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn:
Unsupervised Visuomotor Control through Distributional Planning Networks. Robotics: Science and Systems 2019 - [i24]Tianhe Yu, Gleb Shevchuk, Dorsa Sadigh, Chelsea Finn:
Unsupervised Visuomotor Control through Distributional Planning Networks. CoRR abs/1902.05542 (2019) - [i23]Erdem Biyik, Jonathan Margoliash, Shahrouz Ryan Alimo, Dorsa Sadigh:
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models. CoRR abs/1904.01068 (2019) - [i22]Erdem Biyik, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani:
The Green Choice: Learning and Influencing Human Decisions on Shared Roads. CoRR abs/1904.02209 (2019) - [i21]John Mern, Dorsa Sadigh, Mykel J. Kochenderfer:
Object Exchangeability in Reinforcement Learning: Extended Abstract. CoRR abs/1905.02698 (2019) - [i20]Ashwini Pokle, Roberto Martín-Martín, Patrick Goebel, Vincent Chow, Hans M. Ewald, Junwei Yang, Zhenkai Wang, Amir Sadeghian, Dorsa Sadigh, Silvio Savarese, Marynel Vázquez:
Deep Local Trajectory Replanning and Control for Robot Navigation. CoRR abs/1905.05279 (2019) - [i19]Erdem Biyik, Kenneth Wang, Nima Anari, Dorsa Sadigh:
Batch Active Learning Using Determinantal Point Processes. CoRR abs/1906.07975 (2019) - [i18]Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh:
Learning Reward Functions by Integrating Human Demonstrations and Preferences. CoRR abs/1906.08928 (2019) - [i17]Daniel A. Lazar, Erdem Biyik, Dorsa Sadigh, Ramtin Pedarsani:
Learning How to Dynamically Route Autonomous Vehicles on Shared Roads. CoRR abs/1909.03664 (2019) - [i16]Dylan P. Losey, Dorsa Sadigh:
Robots that Take Advantage of Human Trust. CoRR abs/1909.05777 (2019) - [i15]Dylan P. Losey, Krishnan Srinivasan, Ajay Mandlekar, Animesh Garg, Dorsa Sadigh:
Controlling Assistive Robots with Learned Latent Actions. CoRR abs/1909.09674 (2019) - [i14]Erdem Biyik, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh:
Asking Easy Questions: A User-Friendly Approach to Active Reward Learning. CoRR abs/1910.04365 (2019) - [i13]Dylan P. Losey, Mengxi Li, Jeannette Bohg, Dorsa Sadigh:
Learning from My Partner's Actions: Roles in Decentralized Robot Teams. CoRR abs/1910.07613 (2019) - [i12]Robert X. D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman:
Continual adaptation for efficient machine communication. CoRR abs/1911.09896 (2019) - 2018
- [j2]Dorsa Sadigh, Nick Landolfi, Shankar S. Sastry, Sanjit A. Seshia, Anca D. Dragan:
Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state. Auton. Robots 42(7): 1405-1426 (2018) - [j1]Susmit Jha, Vasumathi Raman, Dorsa Sadigh, Sanjit A. Seshia:
Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic. J. Autom. Reason. 60(1): 43-62 (2018) - [c23]Daniel A. Lazar, Ramtin Pedarsani, Kabir Chandrasekher, Dorsa Sadigh:
Maximizing Road Capacity Using Cars that Influence People. CDC 2018: 1801-1808 - [c22]Erdem Biyik, Dorsa Sadigh:
Batch Active Preference-Based Learning of Reward Functions. CoRL 2018: 519-528 - [c21]Jiaming Song, Hongyu Ren, Dorsa Sadigh, Stefano Ermon:
Multi-Agent Generative Adversarial Imitation Learning. ICLR (Workshop) 2018 - [c20]Jiaming Song, Hongyu Ren, Dorsa Sadigh, Stefano Ermon:
Multi-Agent Generative Adversarial Imitation Learning. NeurIPS 2018: 7472-7483 - [c19]Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Altruistic Autonomy: Beating Congestion on Shared Roads. WAFR 2018: 887-904 - [i11]Daniel A. Lazar, Kabir Chandrasekher, Ramtin Pedarsani, Dorsa Sadigh:
Maximizing Road Capacity Using Cars that Influence People. CoRR abs/1807.04414 (2018) - [i10]Jiaming Song, Hongyu Ren, Dorsa Sadigh, Stefano Ermon:
Multi-Agent Generative Adversarial Imitation Learning. CoRR abs/1807.09936 (2018) - [i9]Erdem Biyik, Dorsa Sadigh:
Batch Active Preference-Based Learning of Reward Functions. CoRR abs/1810.04303 (2018) - [i8]Jaime F. Fisac, Eli Bronstein, Elis Stefansson, Dorsa Sadigh, S. Shankar Sastry, Anca D. Dragan:
Hierarchical Game-Theoretic Planning for Autonomous Vehicles. CoRR abs/1810.05766 (2018) - [i7]Yuhang Che, Allison M. Okamura, Dorsa Sadigh:
Efficient and Trustworthy Social Navigation Via Explicit and Implicit Robot-Human Communication. CoRR abs/1810.11556 (2018) - [i6]Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Altruistic Autonomy: Beating Congestion on Shared Roads. CoRR abs/1810.11978 (2018) - 2017
- [c18]Negar Mehr, Dorsa Sadigh, Roberto Horowitz, S. Shankar Sastry, Sanjit A. Seshia:
Stochastic predictive freeway ramp metering from Signal Temporal Logic specifications. ACC 2017: 4884-4889 - [c17]Dorsa Sadigh, Anca D. Dragan, Shankar Sastry, Sanjit A. Seshia:
Active Preference-Based Learning of Reward Functions. Robotics: Science and Systems 2017 - 2016
- [c16]Negar Mehr, Dorsa Sadigh, Roberto Horowitz:
Probabilistic controller synthesis for freeway traffic networks. ACC 2016: 880 - [c15]Shromona Ghosh, Dorsa Sadigh, Pierluigi Nuzzo, Vasumathi Raman, Alexandre Donzé, Alberto L. Sangiovanni-Vincentelli, S. Shankar Sastry, Sanjit A. Seshia:
Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications. HSCC 2016: 31-40 - [c14]Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Anca D. Dragan:
Information gathering actions over human internal state. IROS 2016: 66-73 - [c13]Tara Rezvani, Katherine Rose Driggs-Campbell, Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Ruzena Bajcsy:
Towards trustworthy automation: User interfaces that convey internal and external awareness. ITSC 2016: 682-688 - [c12]Dorsa Sadigh, Ashish Kapoor:
Safe Control under Uncertainty with Probabilistic Signal Temporal Logic. Robotics: Science and Systems 2016 - [c11]Dorsa Sadigh, Shankar Sastry, Sanjit A. Seshia, Anca D. Dragan:
Planning for Autonomous Cars that Leverage Effects on Human Actions. Robotics: Science and Systems 2016 - [i5]Shromona Ghosh, Dorsa Sadigh, Pierluigi Nuzzo, Vasumathi Raman, Alexandre Donzé, Alberto L. Sangiovanni-Vincentelli, S. Shankar Sastry, Sanjit A. Seshia:
Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications. CoRR abs/1602.01883 (2016) - [i4]Sanjit A. Seshia, Dorsa Sadigh:
Towards Verified Artificial Intelligence. CoRR abs/1606.08514 (2016) - 2015
- [c10]Sanjit A. Seshia, Dorsa Sadigh, S. Shankar Sastry:
Formal methods for semi-autonomous driving. DAC 2015: 148:1-148:5 - [c9]Vasumathi Raman, Alexandre Donzé, Dorsa Sadigh, Richard M. Murray, Sanjit A. Seshia:
Reactive synthesis from signal temporal logic specifications. HSCC 2015: 239-248 - [i3]Dorsa Sadigh, Ashish Kapoor:
Safe Control under Uncertainty. CoRR abs/1510.07313 (2015) - 2014
- [c8]Dorsa Sadigh, Katherine Rose Driggs-Campbell, Alberto Puggelli, Wenchao Li, Victor Shia, Ruzena Bajcsy, Alberto L. Sangiovanni-Vincentelli, S. Shankar Sastry, Sanjit A. Seshia:
Data-Driven Probabilistic Modeling and Verification of Human Driver Behavior. AAAI Spring Symposia 2014 - [c7]Dorsa Sadigh, Eric S. Kim, Samuel Coogan, S. Shankar Sastry, Sanjit A. Seshia:
A learning based approach to control synthesis of Markov decision processes for linear temporal logic specifications. CDC 2014: 1091-1096 - [c6]Dorsa Sadigh, Katherine Rose Driggs-Campbell, Ruzena Bajcsy, S. Shankar Sastry, Sanjit A. Seshia:
User interface design and verification for semi-autonomous driving. HiCoNS 2014: 63-64 - [c5]Ashish Tiwari, Bruno Dutertre, Dejan Jovanovic, Thomas de Candia, Patrick Lincoln, John M. Rushby, Dorsa Sadigh, Sanjit A. Seshia:
Safety envelope for security. HiCoNS 2014: 85-94 - [c4]Wenchao Li, Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia:
Synthesis for Human-in-the-Loop Control Systems. TACAS 2014: 470-484 - [i2]Dorsa Sadigh, Eric S. Kim, Samuel Coogan, S. Shankar Sastry, Sanjit A. Seshia:
A Learning Based Approach to Control Synthesis of Markov Decision Processes for Linear Temporal Logic Specifications. CoRR abs/1409.5486 (2014) - 2013
- [i1]Dorsa Sadigh, Henrik Ohlsson, S. Shankar Sastry, Sanjit A. Seshia:
Robust Subspace System Identification via Weighted Nuclear Norm Optimization. CoRR abs/1312.2132 (2013) - 2012
- [c3]Dorsa Sadigh, Sanjit A. Seshia, Mona Gupta:
Automating exercise generation: a step towards meeting the MOOC challenge for embedded systems. WESE 2012: 2 - 2011
- [c2]Jonathan Kotker, Dorsa Sadigh, Sanjit A. Seshia:
Timing analysis of interrupt-driven programs under context bounds. FMCAD 2011: 81-90 - [c1]Orna Kupferman, Dorsa Sadigh, Sanjit A. Seshia:
Synthesis with Clairvoyance. Haifa Verification Conference 2011: 5-19
Coauthor Index
Montse Gonzalez Arenas
aka: Montserrat Gonzalez Arenas
aka: Montserrat Gonzalez Arenas
[j18] [j16] [i130] [j14] [c95] [c87] [i112] [i94] [i88] [j10] [c84] [c82] [c75] [c70] [c68] [i77] [i75] [i69] [j4] [c67] [c66] [c61] [c57] [c56] [i59] [i58] [i52] [i51] [i50] [i49] [c46] [c44] [c41] [c40] [i39] [i36] [i33] [i31] [i29] [i27] [i25] [c37] [c35] [c33] [c28] [i23] [i22] [i19] [i17] [i14] [c22] [c19] [i9] [i6]
Joey Hejna
aka: Donald Joseph Hejna III
aka: Donald Joseph Hejna III
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