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ORCIDAnca D. Dragan
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- affiliation: UC Berkeley, CA, USA
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2020 – today
- 2024
[c135]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking It for Reward. AAAI 2024: 10066-10073- [c134]Marwa Abdulhai, Micah Carroll, Justin Svegliato, Anca D. Dragan, Sergey Levine:
Defining Deception in Decision Making. AAMAS 2024: 2111-2113 - [c133]Andreea Bobu
, Andi Peng, Pulkit Agrawal, Julie A. Shah, Anca D. Dragan:
Aligning Human and Robot Representations. HRI 2024: 42-54 - [c132]Joey Hong, Anca D. Dragan, Sergey Levine:
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. ICLR 2024 - [c131]Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan:
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. ICLR 2024 - [c130]Ted Moskovitz, Aaditya K. Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca D. Dragan, Stephen Marcus McAleer:
Confronting Reward Model Overoptimization with Constrained RLHF. ICLR 2024 - [c129]Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan:
AI Alignment with Changing and Influenceable Reward Functions. ICML 2024 - [c128]Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca D. Dragan:
Learning to Model the World With Language. ICML 2024 - [c127]Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach:
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. ICML 2024 - [c126]Michelle Pan, Mariah L. Schrum, Vivek Myers, Erdem Biyik, Anca D. Dragan:
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation. ICML 2024 - [c125]Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca D. Dragan, Erdem Biyik:
A Generalized Acquisition Function for Preference-based Reward Learning. ICRA 2024: 2814-2821 - [c124]Minae Kwon, Hengyuan Hu, Vivek Myers, Siddharth Karamcheti, Anca D. Dragan, Dorsa Sadigh:
Toward Grounded Commonsense Reasoning. ICRA 2024: 5463-5470 - [i124]Leon Lang, Davis Foote, Stuart Russell, Anca D. Dragan, Erik Jenner, Scott Emmons:
When Your AIs Deceive You: Challenges with Partial Observability of Human Evaluators in Reward Learning. CoRR abs/2402.17747 (2024) - [i123]Cassidy Laidlaw, Shivam Singhal, Anca D. Dragan:
Preventing Reward Hacking with Occupancy Measure Regularization. CoRR abs/2403.03185 (2024) - [i122]Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca D. Dragan, Erdem Biyik:
A Generalized Acquisition Function for Preference-based Reward Learning. CoRR abs/2403.06003 (2024) - [i121]Mary Phuong, Matthew Aitchison, Elliot Catt, Sarah Cogan, Alexandre Kaskasoli, Victoria Krakovna, David Lindner, Matthew Rahtz, Yannis Assael, Sarah Hodkinson, Heidi Howard, Tom Lieberum, Ramana Kumar, Maria Abi Raad, Albert Webson, Lewis Ho, Sharon Lin, Sebastian Farquhar, Marcus Hutter, Grégoire Delétang, Anian Ruoss, Seliem El-Sayed, Sasha Brown, Anca D. Dragan, Rohin Shah, Allan Dafoe, Toby Shevlane:
Evaluating Frontier Models for Dangerous Capabilities. CoRR abs/2403.13793 (2024) - [i120]Jerry Zhi-Yang He, Sashrika Pandey, Mariah L. Schrum, Anca D. Dragan:
CoS: Enhancing Personalization and Mitigating Bias with Context Steering. CoRR abs/2405.01768 (2024) - [i119]Micah Carroll, Davis Foote, Anand Siththaranjan, Stuart Russell, Anca D. Dragan:
AI Alignment with Changing and Influenceable Reward Functions. CoRR abs/2405.17713 (2024) - [i118]Michelle Pan, Mariah Schrum, Vivek Myers, Erdem Biyik, Anca D. Dragan:
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation. CoRR abs/2406.06714 (2024) - [i117]Erik Jones, Anca D. Dragan, Jacob Steinhardt:
Adversaries Can Misuse Combinations of Safe Models. CoRR abs/2406.14595 (2024) - [i116]Vivek Myers, Chongyi Zheng, Anca D. Dragan, Sergey Levine, Benjamin Eysenbach:
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making. CoRR abs/2406.17098 (2024) - [i115]Tom Lieberum, Senthooran Rajamanoharan, Arthur Conmy, Lewis Smith, Nicolas Sonnerat, Vikrant Varma, János Kramár, Anca D. Dragan, Rohin Shah, Neel Nanda:
Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2. CoRR abs/2408.05147 (2024) - [i114]Zhaojing Yang, Miru Jun, Jeremy Tien, Stuart J. Russell, Anca D. Dragan, Erdem Biyik:
Trajectory Improvement and Reward Learning from Comparative Language Feedback. CoRR abs/2410.06401 (2024) - [i113]Marcus Williams, Micah Carroll, Adhyyan Narang, Constantin Weisser, Brendan Murphy, Anca D. Dragan:
On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback. CoRR abs/2411.02306 (2024) - [i112]Vivek Myers, Evan Ellis, Sergey Levine, Benjamin Eysenbach, Anca D. Dragan:
Learning to Assist Humans without Inferring Rewards. CoRR abs/2411.02623 (2024) - [i111]Joey Hong, Anca D. Dragan, Sergey Levine:
Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning. CoRR abs/2411.05193 (2024) - [i110]Joey Hong, Jessica Lin, Anca D. Dragan, Sergey Levine:
Interactive Dialogue Agents via Reinforcement Learning on Hindsight Regenerations. CoRR abs/2411.05194 (2024) - 2023
- [j20]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) - [j19]Daniel Shin, Anca D. Dragan, Daniel S. Brown:
Benchmarks and Algorithms for Offline Preference-Based Reward Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c123]Gaurav R. Ghosal, Matthew Zurek, Daniel S. Brown, Anca D. Dragan:
The Effect of Modeling Human Rationality Level on Learning Rewards from Multiple Feedback Types. AAAI 2023: 5983-5992 - [c122]Jerry Zhi-Yang He, Daniel S. Brown, Zackory Erickson, Anca D. Dragan:
Quantifying Assistive Robustness Via the Natural-Adversarial Frontier. CoRL 2023: 1865-1886 - [c121]Vivek Myers, Andre Wang He, Kuan Fang, Homer Rich Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine:
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRL 2023: 3894-3908 - [c120]Ran Tian, Masayoshi Tomizuka, Anca D. Dragan, Andrea Bajcsy:
Towards Modeling and Influencing the Dynamics of Human Learning. HRI 2023: 350-358 - [c119]Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan:
SIRL: Similarity-based Implicit Representation Learning. HRI 2023: 565-574 - [c118]Joey Hong, Kush Bhatia, Anca D. Dragan:
On the Sensitivity of Reward Inference to Misspecified Human Models. ICLR 2023 - [c117]Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca D. Dragan, Daniel S. Brown:
Causal Confusion and Reward Misidentification in Preference-Based Reward Learning. ICLR 2023 - [c116]Gaurav Rohit Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan:
Contextual Reliability: When Different Features Matter in Different Contexts. ICML 2023: 11300-11320 - [c115]Erik Jones, Anca D. Dragan, Aditi Raghunathan, Jacob Steinhardt:
Automatically Auditing Large Language Models via Discrete Optimization. ICML 2023: 15307-15329 - [c114]Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine:
Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning. IROS 2023: 7523-7530 - [c113]Joey Hong, Sergey Levine, Anca D. Dragan:
Learning to Influence Human Behavior with Offline Reinforcement Learning. NeurIPS 2023 - [c112]Cassidy Laidlaw, Stuart J. Russell, Anca D. Dragan:
Bridging RL Theory and Practice with the Effective Horizon. NeurIPS 2023 - [i109]Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan:
SIRL: Similarity-based Implicit Representation Learning. CoRR abs/2301.00810 (2023) - [i108]Ran Tian, Masayoshi Tomizuka, Anca D. Dragan, Andrea Bajcsy:
Towards Modeling and Influencing the Dynamics of Human Learning. CoRR abs/2301.00901 (2023) - [i107]Daniel Shin, Anca D. Dragan, Daniel S. Brown:
Benchmarks and Algorithms for Offline Preference-Based Reward Learning. CoRR abs/2301.01392 (2023) - [i106]Andreea Bobu, Andi Peng, Pulkit Agrawal, Julie Shah, Anca D. Dragan:
Aligning Robot and Human Representations. CoRR abs/2302.01928 (2023) - [i105]Joey Hong, Anca D. Dragan, Sergey Levine:
Learning to Influence Human Behavior with Offline Reinforcement Learning. CoRR abs/2303.02265 (2023) - [i104]Erik Jones, Anca D. Dragan, Aditi Raghunathan, Jacob Steinhardt:
Automatically Auditing Large Language Models via Discrete Optimization. CoRR abs/2303.04381 (2023) - [i103]Cassidy Laidlaw, Stuart Russell, Anca D. Dragan:
Bridging RL Theory and Practice with the Effective Horizon. CoRR abs/2304.09853 (2023) - [i102]Smitha Milli, Micah Carroll, Sashrika Pandey, Yike Wang, Anca D. Dragan:
Twitter's Algorithm: Amplifying Anger, Animosity, and Affective Polarization. CoRR abs/2305.16941 (2023) - [i101]Minae Kwon, Hengyuan Hu, Vivek Myers, Siddharth Karamcheti, Anca D. Dragan, Dorsa Sadigh:
Toward Grounded Social Reasoning. CoRR abs/2306.08651 (2023) - [i100]Vivek Myers, Andre He, Kuan Fang, Homer Walke, Philippe Hansen-Estruch, Ching-An Cheng, Mihai Jalobeanu, Andrey Kolobov, Anca D. Dragan, Sergey Levine:
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control. CoRR abs/2307.00117 (2023) - [i99]Gaurav R. Ghosal, Amrith Setlur, Daniel S. Brown, Anca D. Dragan, Aditi Raghunathan:
Contextual Reliability: When Different Features Matter in Different Contexts. CoRR abs/2307.10026 (2023) - [i98]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) - [i97]Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca D. Dragan:
Learning to Model the World with Language. CoRR abs/2308.01399 (2023) - [i96]Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine:
Bootstrapping Adaptive Human-Machine Interfaces with Offline Reinforcement Learning. CoRR abs/2309.03839 (2023) - [i95]W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum:
Learning Optimal Advantage from Preferences and Mistaking it for Reward. CoRR abs/2310.02456 (2023) - [i94]Ted Moskovitz, Aaditya K. Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca D. Dragan, Stephen McAleer:
Confronting Reward Model Overoptimization with Constrained RLHF. CoRR abs/2310.04373 (2023) - [i93]Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Anca D. Dragan:
Quantifying Assistive Robustness Via the Natural-Adversarial Frontier. CoRR abs/2310.10610 (2023) - [i92]Yoshua Bengio, Geoffrey E. Hinton, Andrew Yao, Dawn Song, Pieter Abbeel, Yuval Noah Harari, Ya-Qin Zhang, Lan Xue, Shai Shalev-Shwartz, Gillian K. Hadfield, Jeff Clune, Tegan Maharaj, Frank Hutter, Atilim Günes Baydin, Sheila A. McIlraith, Qiqi Gao, Ashwin Acharya, David Krueger, Anca D. Dragan, Philip H. S. Torr, Stuart Russell, Daniel Kahneman, Jan Brauner, Sören Mindermann:
Managing AI Risks in an Era of Rapid Progress. CoRR abs/2310.17688 (2023) - [i91]Joey Hong, Anca D. Dragan, Sergey Levine:
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity. CoRR abs/2310.20663 (2023) - [i90]Joey Hong, Sergey Levine, Anca D. Dragan:
Zero-Shot Goal-Directed Dialogue via RL on Imagined Conversations. CoRR abs/2311.05584 (2023) - [i89]Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan:
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. CoRR abs/2312.08369 (2023) - 2022
- [j18]Dylan P. Losey, Andrea Bajcsy, Marcia K. O'Malley, Anca D. Dragan:
Physical interaction as communication: Learning robot objectives online from human corrections. Int. J. Robotics Res. 41(1): 20-44 (2022) - [j17]Andreea Bobu, Marius Wiggert, Claire J. Tomlin, Anca D. Dragan:
Inducing structure in reward learning by learning features. Int. J. Robotics Res. 41(5): 497-518 (2022) - [c111]Jessy Lin, Daniel Fried, Dan Klein, Anca D. Dragan:
Inferring Rewards from Language in Context. ACL (1) 2022: 8546-8560 - [c110]Jerry Zhi-Yang He, Zackory Erickson, Daniel S. Brown, Aditi Raghunathan, Anca D. Dragan:
Learning Representations that Enable Generalization in Assistive Tasks. CoRL 2022: 2105-2114 - [c109]Cassidy Laidlaw, Anca D. Dragan:
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models. ICLR 2022 - [c108]Micah D. Carroll, Anca D. Dragan, Stuart Russell, Dylan Hadfield-Menell:
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. ICML 2022: 2686-2708 - [c107]Sean Chen, Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine:
ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning. ICRA 2022: 7505-7512 - [c106]Ran Tian, Liting Sun, Andrea Bajcsy, Masayoshi Tomizuka, Anca D. Dragan:
Safety Assurances for Human-Robot Interaction via Confidence-aware Game-theoretic Human Models. ICRA 2022: 11229-11235 - [c105]Arjun Sripathy, Andreea Bobu, Zhongyu Li, Koushil Sreenath, Daniel S. Brown, Anca D. Dragan:
Teaching Robots to Span the Space of Functional Expressive Motion. IROS 2022: 13406-13413 - [c104]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Uni[MASK]: Unified Inference in Sequential Decision Problems. NeurIPS 2022 - [c103]Siddharth Reddy, Sergey Levine, Anca D. Dragan:
First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization. NeurIPS 2022 - [i88]Andreea Bobu, Marius Wiggert, Claire J. Tomlin, Anca D. Dragan:
Inducing Structure in Reward Learning by Learning Features. CoRR abs/2201.07082 (2022) - [i87]Sean Chen, Jensen Gao, Siddharth Reddy, Glen Berseth, Anca D. Dragan, Sergey Levine:
ASHA: Assistive Teleoperation via Human-in-the-Loop Reinforcement Learning. CoRR abs/2202.02465 (2022) - [i86]Jensen Gao, Siddharth Reddy, Glen Berseth, Nicholas Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca D. Dragan, Sergey Levine:
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback. CoRR abs/2203.02072 (2022) - [i85]Arjun Sripathy, Andreea Bobu, Zhongyu Li, Koushil Sreenath, Daniel S. Brown, Anca D. Dragan:
Teaching Robots to Span the Space of Functional Expressive Motion. CoRR abs/2203.02091 (2022) - [i84]Jessy Lin, Daniel Fried, Dan Klein, Anca D. Dragan:
Inferring Rewards from Language in Context. CoRR abs/2204.02515 (2022) - [i83]Jeremy Tien, Jerry Zhi-Yang He, Zackory Erickson, Anca D. Dragan, Daniel S. Brown:
A Study of Causal Confusion in Preference-Based Reward Learning. CoRR abs/2204.06601 (2022) - [i82]Cassidy Laidlaw, Anca D. Dragan:
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models. CoRR abs/2204.10759 (2022) - [i81]Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
Estimating and Penalizing Induced Preference Shifts in Recommender Systems. CoRR abs/2204.11966 (2022) - [i80]Micah Carroll, Jessy Lin, Orr Paradise, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
Towards Flexible Inference in Sequential Decision Problems via Bidirectional Transformers. CoRR abs/2204.13326 (2022) - [i79]Siddharth Reddy, Sergey Levine, Anca D. Dragan:
First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization. CoRR abs/2205.12381 (2022) - [i78]Gaurav R. Ghosal, Matthew Zurek, Daniel S. Brown, Anca D. Dragan:
The Effect of Modeling Human Rationality Level on Learning Rewards from Multiple Feedback Types. CoRR abs/2208.10687 (2022) - [i77]Mesut Yang, Micah Carroll, Anca D. Dragan:
Optimal Behavior Prior: Data-Efficient Human Models for Improved Human-AI Collaboration. CoRR abs/2211.01602 (2022) - [i76]Micah Carroll, Orr Paradise, Jessy Lin, Raluca Georgescu, Mingfei Sun, David Bignell, Stephanie Milani, Katja Hofmann, Matthew J. Hausknecht, Anca D. Dragan, Sam Devlin:
UniMASK: Unified Inference in Sequential Decision Problems. CoRR abs/2211.10869 (2022) - [i75]David Zhang, Micah Carroll, Andreea Bobu, Anca D. Dragan:
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking. CoRR abs/2212.00169 (2022) - [i74]Jerry Zhi-Yang He, Aditi Raghunathan, Daniel S. Brown, Zackory Erickson, Anca D. Dragan:
Learning Representations that Enable Generalization in Assistive Tasks. CoRR abs/2212.03175 (2022) - [i73]Joey Hong, Kush Bhatia, Anca D. Dragan:
On the Sensitivity of Reward Inference to Misspecified Human Models. CoRR abs/2212.04717 (2022) - 2021
- [j16]Andrea Bajcsy, Somil Bansal, Ellis Ratner, Claire J. Tomlin, Anca D. Dragan:
A Robust Control Framework for Human Motion Prediction. IEEE Robotics Autom. Lett. 6(1): 24-31 (2021) - [j15]Ellis Ratner, Andrea Bajcsy, Terrence Fong, Claire J. Tomlin, Anca D. Dragan:
Efficient Dynamics Estimation With Adaptive Model Sets. IEEE Robotics Autom. Lett. 6(2): 2373-2380 (2021) - [j14]Maartje M. A. de Graaf, Anca D. Dragan, Bertram F. Malle, Tom Ziemke:
Introduction to the Special Issue on Explainable Robotic Systems. ACM Trans. Hum. Robot Interact. 10(3): 22:1-22:4 (2021) - [c102]Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah:
Evaluating the Robustness of Collaborative Agents. AAMAS 2021: 1560-1562 - [c101]Jerry Zhi-Yang He, Anca D. Dragan:
Assisted Robust Reward Design. CoRL 2021: 1234-1246 - [c100]Andreea Bobu, Marius Wiggert, Claire J. Tomlin, Anca D. Dragan:
Feature Expansive Reward Learning: Rethinking Human Input. HRI 2021: 216-224 - [c99]Jensen Gao, Siddharth Reddy, Glen Berseth, Nicholas Hardy, Nikhilesh Natraj, Karunesh Ganguly, Anca D. Dragan, Sergey Levine:
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback. ICLR 2021 - [c98]David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan:
Learning What To Do by Simulating the Past. ICLR 2021 - [c97]Daniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum:
Value Alignment Verification. ICML 2021: 1105-1115 - [c96]Zaynah Javed, Daniel S. Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca D. Dragan, Ken Goldberg:
Policy Gradient Bayesian Robust Optimization for Imitation Learning. ICML 2021: 4785-4796 - [c95]Andrea Bajcsy, Anand Siththaranjan, Claire J. Tomlin, Anca D. Dragan:
Analyzing Human Models that Adapt Online. ICRA 2021: 2754-2760 - [c94]Matthew Zurek, Andreea Bobu, Daniel S. Brown, Anca D. Dragan:
Situational Confidence Assistance for Lifelong Shared Autonomy. ICRA 2021: 2783-2789 - [c93]Arjun Sripathy, Andreea Bobu, Daniel S. Brown, Anca D. Dragan:
Dynamically Switching Human Prediction Models for Efficient Planning. ICRA 2021: 3495-3501 - [c92]Kush Bhatia, Peter L. Bartlett, Anca D. Dragan, Jacob Steinhardt:
Agnostic Learning with Unknown Utilities. ITCS 2021: 55:1-55:20 - [c91]Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan:
Optimal Cost Design for Model Predictive Control. L4DC 2021: 1205-1217 - [c90]Kimin Lee, Laura M. Smith, Anca D. Dragan, Pieter Abbeel:
B-Pref: Benchmarking Preference-Based Reinforcement Learning. NeurIPS Datasets and Benchmarks 2021 - [c89]Siddharth Reddy, Anca D. Dragan, Sergey Levine:
Pragmatic Image Compression for Human-in-the-Loop Decision-Making. NeurIPS 2021: 26499-26510 - [c88]Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
Estimating and Penalizing Preference Shift in Recommender Systems. RecSys 2021: 661-667 - [c87]Liting Sun, Xiaogang Jia, Anca D. Dragan:
On complementing end-to-end human behavior predictors with planning. Robotics: Science and Systems 2021 - [i72]Paul Knott, Micah Carroll, Sam Devlin, Kamil Ciosek, Katja Hofmann, Anca D. Dragan, Rohin Shah:
Evaluating the Robustness of Collaborative Agents. CoRR abs/2101.05507 (2021) - [i71]Rachel Freedman, Rohin Shah, Anca D. Dragan:
Choice Set Misspecification in Reward Inference. CoRR abs/2101.07691 (2021) - [i70]Liting Sun, Xiaogang Jia, Anca D. Dragan:
On complementing end-to-end human motion predictors with planning. CoRR abs/2103.05661 (2021) - [i69]Andrea Bajcsy, Anand Siththaranjan, Claire J. Tomlin, Anca D. Dragan:
Analyzing Human Models that Adapt Online. CoRR abs/2103.05746 (2021) - [i68]Arjun Sripathy, Andreea Bobu, Daniel S. Brown, Anca D. Dragan:
Dynamically Switching Human Prediction Models for Efficient Planning. CoRR abs/2103.07815 (2021) - [i67]David Lindner, Rohin Shah, Pieter Abbeel, Anca D. Dragan:
Learning What To Do by Simulating the Past. CoRR abs/2104.03946 (2021) - [i66]Matthew Zurek, Andreea Bobu, Daniel S. Brown, Anca D. Dragan:
Situational Confidence Assistance for Lifelong Shared Autonomy. CoRR abs/2104.06556 (2021) - [i65]Kush Bhatia, Peter L. Bartlett, Anca D. Dragan, Jacob Steinhardt:
Agnostic learning with unknown utilities. CoRR abs/2104.08482 (2021) - [i64]Avik Jain, Lawrence Chan, Daniel S. Brown, Anca D. Dragan:
Optimal Cost Design for Model Predictive Control. CoRR abs/2104.11353 (2021) - [i63]Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, Martin J. Wainwright:
Preference learning along multiple criteria: A game-theoretic perspective. CoRR abs/2105.01850 (2021) - [i62]Zaynah Javed, Daniel S. Brown, Satvik Sharma, Jerry Zhu, Ashwin Balakrishna, Marek Petrik, Anca D. Dragan, Ken Goldberg:
Policy Gradient Bayesian Robust Optimization for Imitation Learning. CoRR abs/2106.06499 (2021) - [i61]Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William H. Guss, Sharada P. Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca D. Dragan:
The MineRL BASALT Competition on Learning from Human Feedback. CoRR abs/2107.01969 (2021) - [i60]Dylan P. Losey, Andrea Bajcsy, Marcia K. O'Malley, Anca D. Dragan:
Physical Interaction as Communication: Learning Robot Objectives Online from Human Corrections. CoRR abs/2107.02349 (2021) - [i59]Siddharth Reddy, Anca D. Dragan, Sergey Levine:
Pragmatic Image Compression for Human-in-the-Loop Decision-Making. CoRR abs/2108.04219 (2021) - [i58]Ran Tian, Liting Sun, Andrea Bajcsy, Masayoshi Tomizuka, Anca D. Dragan:
Safety Assurances for Human-Robot Interaction via Confidence-aware Game-theoretic Human Models. CoRR abs/2109.14700 (2021) - [i57]Kimin Lee, Laura M. Smith, Anca D. Dragan, Pieter Abbeel:
B-Pref: Benchmarking Preference-Based Reinforcement Learning. CoRR abs/2111.03026 (2021) - [i56]Lawrence Chan, Andrew Critch, Anca D. Dragan:
Human irrationality: both bad and good for reward inference. CoRR abs/2111.06956 (2021) - [i55]Jerry Zhi-Yang He, Anca D. Dragan:
Assisted Robust Reward Design. CoRR abs/2111.09884 (2021) - 2020
- [j13]Vael Gates, Thomas L. Griffiths, Anca D. Dragan:
How to Be Helpful to Multiple People at Once. Cogn. Sci. 44(6) (2020) - [j12]David Fridovich-Keil, Andrea Bajcsy, Jaime F. Fisac, Sylvia L. Herbert, Steven Wang, Anca D. Dragan, Claire J. Tomlin:
Confidence-aware motion prediction for real-time collision avoidance1. Int. J. Robotics Res. 39(2-3) (2020) - [j11]Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac, Sampada Deglurkar, Anca D. Dragan:
Quantifying Hypothesis Space Misspecification in Learning From Human-Robot Demonstrations and Physical Corrections. IEEE Trans. Robotics 36(3): 835-854 (2020) - [c86]Siddharth Reddy, Sergey Levine, Anca D. Dragan:
Assisted Perception: Optimizing Observations to Communicate State. CoRL 2020: 748-764 - [c85]Andreea Bobu, Dexter R. R. Scobee, Jaime F. Fisac, S. Shankar Sastry, Anca D. Dragan:
LESS is More: Rethinking Probabilistic Models of Human Behavior. HRI 2020: 429-437 - [c84]Siddharth Reddy, Anca D. Dragan, Sergey Levine:
SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards. ICLR 2020 - [c83]Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shane Legg, Jan Leike:
Learning Human Objectives by Evaluating Hypothetical Behavior. ICML 2020: 8020-8029 - [c82]David Fridovich-Keil, Ellis Ratner, Lasse Peters, Anca D. Dragan, Claire J. Tomlin:
Efficient Iterative Linear-Quadratic Approximations for Nonlinear Multi-Player General-Sum Differential Games. ICRA 2020: 1475-1481 - [c81]Gokul Swamy, Siddharth Reddy, Sergey Levine, Anca D. Dragan:
Scaled Autonomy: Enabling Human Operators to Control Robot Fleets. ICRA 2020: 5942-5948 - [c80]Somil Bansal, Andrea Bajcsy, Ellis Ratner, Anca D. Dragan, Claire J. Tomlin:
A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning. ICRA 2020: 7149-7155 - [c79]Rachel Freedman, Rohin Shah, Anca D. Dragan:
Choice Set Misspecification in Reward Inference. AISafety@IJCAI 2020 - [c78]Kush Bhatia, Ashwin Pananjady, Peter L. Bartlett, Anca D. Dragan, Martin J. Wainwright:
Preference learning along multiple criteria: A game-theoretic perspective. NeurIPS 2020 - [c77]Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca D. Dragan:
AvE: Assistance via Empowerment. NeurIPS 2020 - [c76]Hong Jun Jeon, Smitha Milli, Anca D. Dragan:
Reward-rational (implicit) choice: A unifying formalism for reward learning. NeurIPS 2020 - [i54]Andreea Bobu, Dexter R. R. Scobee, Jaime F. Fisac, S. Shankar Sastry, Anca D. Dragan:
LESS is More: Rethinking Probabilistic Models of Human Behavior. CoRR abs/2001.04465 (2020) - [i53]Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac, Sampada Deglurkar, Anca D. Dragan:
Quantifying Hypothesis Space Misspecification in Learning from Human-Robot Demonstrations and Physical Corrections. CoRR abs/2002.00941 (2020) - [i52]Hong Jun Jeon, Smitha Milli, Anca D. Dragan:
Reward-rational (implicit) choice: A unifying formalism for reward learning. CoRR abs/2002.04833 (2020) - [i51]Andreea Bobu, Marius Wiggert, Claire J. Tomlin, Anca D. Dragan:
Feature Expansive Reward Learning: Rethinking Human Input. CoRR abs/2006.13208 (2020) - [i50]Yuqing Du, Stas Tiomkin, Emre Kiciman, Daniel Polani, Pieter Abbeel, Anca D. Dragan:
AvE: Assistance via Empowerment. CoRR abs/2006.14796 (2020) - [i49]Siddharth Reddy, Sergey Levine, Anca D. Dragan:
Assisted Perception: Optimizing Observations to Communicate State. CoRR abs/2008.02840 (2020)
2010 – 2019
- 2019
- [j10]Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan:
Enabling robots to communicate their objectives. Auton. Robots 43(2): 309-326 (2019) - [c75]Anca D. Dragan:
Specifying AI Objectives as a Human-AI Collaboration problem. AIES 2019: 329 - [c74]Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan:
Human-AI Learning Performance in Multi-Armed Bandits. AIES 2019: 369-375 - [c73]Sandy H. Huang, Isabella Huang, Ravi Pandya, Anca D. Dragan:
Nonverbal Robot Feedback for Human Teachers. CoRL 2019: 1038-1051 - [c72]Smitha Milli, Ludwig Schmidt, Anca D. Dragan, Moritz Hardt:
Model Reconstruction from Model Explanations. FAT 2019: 1-9 - [c71]Smitha Milli, John Miller, Anca D. Dragan, Moritz Hardt:
The Social Cost of Strategic Classification. FAT 2019: 230-239 - [c70]Rohan Choudhury, Gokul Swamy, Dylan Hadfield-Menell, Anca D. Dragan:
On the Utility of Model Learning in HRI. HRI 2019: 317-325 - [c69]Lawrence Chan, Dylan Hadfield-Menell, Siddhartha S. Srinivasa, Anca D. Dragan:
The Assistive Multi-Armed Bandit. HRI 2019: 354-363 - [c68]Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan:
Preferences Implicit in the State of the World. ICLR (Poster) 2019 - [c67]Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca D. Dragan:
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference. ICML 2019: 5670-5679 - [c66]Kelvin Xu, Ellis Ratner, Anca D. Dragan, Sergey Levine, Chelsea Finn:
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. ICML 2019: 6952-6962 - [c65]Andrea Bajcsy, Sylvia L. Herbert, David Fridovich-Keil, Jaime F. Fisac, Sampada Deglurkar, Anca D. Dragan, Claire J. Tomlin:
A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance. ICRA 2019: 936-943 - [c64]Jason Y. Zhang, Anca D. Dragan:
Learning from Extrapolated Corrections. ICRA 2019: 7034-7040 - [c63]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 - [c62]Micah Carroll, Rohin Shah, Mark K. Ho, Tom Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan:
On the Utility of Learning about Humans for Human-AI Coordination. NeurIPS 2019: 5175-5186 - [c61]Smitha Milli, Anca D. Dragan:
Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning. UAI 2019: 925-934 - [i48]Rohan Choudhury, Gokul Swamy, Dylan Hadfield-Menell, Anca D. Dragan:
On the Utility of Model Learning in HRI. CoRR abs/1901.01291 (2019) - [i47]Lawrence Chan, Dylan Hadfield-Menell, Siddhartha S. Srinivasa, Anca D. Dragan:
The Assistive Multi-Armed Bandit. CoRR abs/1901.08654 (2019) - [i46]Rohin Shah, Dmitrii Krasheninnikov, Jordan Alexander, Pieter Abbeel, Anca D. Dragan:
Preferences Implicit in the State of the World. CoRR abs/1902.04198 (2019) - [i45]Smitha Milli, Anca D. Dragan:
Literal or Pedagogic Human? Analyzing Human Model Misspecification in Objective Learning. CoRR abs/1903.03877 (2019) - [i44]Siddharth Reddy, Anca D. Dragan, Sergey Levine:
SQIL: Imitation Learning via Regularized Behavioral Cloning. CoRR abs/1905.11108 (2019) - [i43]Matthew Rahtz, James Fang, Anca D. Dragan, Dylan Hadfield-Menell:
An Extensible Interactive Interface for Agent Design. CoRR abs/1906.02641 (2019) - [i42]Rohin Shah, Noah Gundotra, Pieter Abbeel, Anca D. Dragan:
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference. CoRR abs/1906.09624 (2019) - [i41]Kush Bhatia, Yi-An Ma, Anca D. Dragan, Peter L. Bartlett, Michael I. Jordan:
Bayesian Robustness: A Nonasymptotic Viewpoint. CoRR abs/1907.11826 (2019) - [i40]David Fridovich-Keil, Ellis Ratner, Anca D. Dragan, Claire J. Tomlin:
Efficient Iterative Linear-Quadratic Approximations for Nonlinear Multi-Player General-Sum Differential Games. CoRR abs/1909.04694 (2019) - [i39]Gokul Swamy, Siddharth Reddy, Sergey Levine, Anca D. Dragan:
Scaled Autonomy: Enabling Human Operators to Control Robot Fleets. CoRR abs/1910.02910 (2019) - [i38]Micah Carroll, Rohin Shah, Mark K. Ho, Thomas L. Griffiths, Sanjit A. Seshia, Pieter Abbeel, Anca D. Dragan:
On the Utility of Learning about Humans for Human-AI Coordination. CoRR abs/1910.05789 (2019) - [i37]Somil Bansal, Andrea Bajcsy, Ellis Ratner, Anca D. Dragan, Claire J. Tomlin:
A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning. CoRR abs/1910.13369 (2019) - [i36]Sandy H. Huang, Isabella Huang, Ravi Pandya, Anca D. Dragan:
Nonverbal Robot Feedback for Human Teachers. CoRR abs/1911.02320 (2019) - [i35]Siddharth Reddy, Anca D. Dragan, Sergey Levine, Shane Legg, Jan Leike:
Learning Human Objectives by Evaluating Hypothetical Behavior. CoRR abs/1912.05652 (2019) - 2018
- [j9]Leonel Dario Rozo, Heni Ben Amor, Sylvain Calinon, Anca D. Dragan, Dongheui Lee:
Special issue on learning for human-robot collaboration. Auton. Robots 42(5): 953-956 (2018) - [j8]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) - [c60]Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac, Anca D. Dragan:
Learning under Misspecified Objective Spaces. CoRL 2018: 796-805 - [c59]Minae Kwon, Sandy H. Huang, Anca D. Dragan:
Expressing Robot Incapability. HRI 2018: 87-95 - [c58]Chandrayee Basu, Mukesh Singhal, Anca D. Dragan:
Learning from Richer Human Guidance: Augmenting Comparison-Based Learning with Feature Queries. HRI 2018: 132-140 - [c57]Andrea Bajcsy, Dylan P. Losey, Marcia K. O'Malley, Anca D. Dragan:
Learning from Physical Human Corrections, One Feature at a Time. HRI 2018: 141-149 - [c56]Maartje M. A. de Graaf, Bertram F. Malle, Anca D. Dragan, Tom Ziemke:
Explainable Robotic Systems. HRI (Companion) 2018: 387-388 - [c55]Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning. ICML 2018: 3391-3399 - [c54]Aaron M. Bestick, Ravi Pandya, Ruzena Bajcsy, Anca D. Dragan:
Learning Human Ergonomic Preferences for Handovers. ICRA 2018: 1-9 - [c53]Liting Sun, Wei Zhan, Masayoshi Tomizuka, Anca D. Dragan:
Courteous Autonomous Cars. IROS 2018: 663-670 - [c52]Allan Zhou, Anca D. Dragan:
Cost Functions for Robot Motion Style. IROS 2018: 3632-3639 - [c51]Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan:
Establishing Appropriate Trust via Critical States. IROS 2018: 3929-3936 - [c50]Hong Jun Jeon, Anca D. Dragan:
Configuration Space Metrics. IROS 2018: 5101-5108 - [c49]Nicholas C. Landolfi, Anca D. Dragan:
Social Cohesion in Autonomous Driving. IROS 2018: 8118-8125 - [c48]Siddharth Reddy, Anca D. Dragan, Sergey Levine:
Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior. NeurIPS 2018: 1461-1472 - [c47]Jaime F. Fisac, Andrea Bajcsy, Sylvia L. Herbert, David Fridovich-Keil, Steven Wang, Claire J. Tomlin, Anca D. Dragan:
Probabilistically Safe Robot Planning with Confidence-Based Human Predictions. Robotics: Science and Systems 2018 - [c46]Ellis Ratner, Dylan Hadfield-Menell, Anca D. Dragan:
Simplifying Reward Design through Divide-and-Conquer. Robotics: Science and Systems 2018 - [c45]Siddharth Reddy, Anca D. Dragan, Sergey Levine:
Shared Autonomy via Deep Reinforcement Learning. Robotics: Science and Systems 2018 - [i34]Allan Zhou, Dylan Hadfield-Menell, Anusha Nagabandi, Anca D. Dragan:
Expressive Robot Motion Timing. CoRR abs/1802.01536 (2018) - [i33]Chandrayee Basu, Mukesh Singhal, Anca D. Dragan:
Learning from Richer Human Guidance: Augmenting Comparison-Based Learning with Feature Queries. CoRR abs/1802.01604 (2018) - [i32]Chandrayee Basu, Qian Yang, David Hungerman, Mukesh Singhal, Anca D. Dragan:
Do You Want Your Autonomous Car To Drive Like You? CoRR abs/1802.01636 (2018) - [i31]Siddharth Reddy, Sergey Levine, Anca D. Dragan:
Shared Autonomy via Deep Reinforcement Learning. CoRR abs/1802.01744 (2018) - [i30]Chang Liu, Jessica B. Hamrick, Jaime F. Fisac, Anca D. Dragan, J. Karl Hedrick, S. Shankar Sastry, Thomas L. Griffiths:
Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration. CoRR abs/1802.01780 (2018) - [i29]Jaime F. Fisac, Chang Liu, Jessica B. Hamrick, S. Shankar Sastry, J. Karl Hedrick, Thomas L. Griffiths, Anca D. Dragan:
Generating Plans that Predict Themselves. CoRR abs/1802.05250 (2018) - [i28]Siddharth Reddy, Anca D. Dragan, Sergey Levine:
Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior. CoRR abs/1805.08010 (2018) - [i27]Kelvin Xu, Ellis Ratner, Anca D. Dragan, Sergey Levine, Chelsea Finn:
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. CoRR abs/1805.12573 (2018) - [i26]Jaime F. Fisac, Andrea Bajcsy, Sylvia L. Herbert, David Fridovich-Keil, Steven Wang, Claire J. Tomlin, Anca D. Dragan:
Probabilistically Safe Robot Planning with Confidence-Based Human Predictions. CoRR abs/1806.00109 (2018) - [i25]Ellis Ratner, Dylan Hadfield-Menell, Anca D. Dragan:
Simplifying Reward Design through Divide-and-Conquer. CoRR abs/1806.02501 (2018) - [i24]Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart Russell, Anca D. Dragan:
An Efficient, Generalized Bellman Update For Cooperative Inverse Reinforcement Learning. CoRR abs/1806.03820 (2018) - [i23]Smitha Milli, Ludwig Schmidt, Anca D. Dragan, Moritz Hardt:
Model Reconstruction from Model Explanations. CoRR abs/1807.05185 (2018) - [i22]Liting Sun, Wei Zhan, Masayoshi Tomizuka, Anca D. Dragan:
Courteous Autonomous Cars. CoRR abs/1808.02633 (2018) - [i21]Nicholas C. Landolfi, Anca D. Dragan:
Social Cohesion in Autonomous Driving. CoRR abs/1808.03845 (2018) - [i20]Hong Jun Jeon, Anca D. Dragan:
Configuration Space Metrics. CoRR abs/1808.03891 (2018) - [i19]Smitha Milli, John Miller, Anca D. Dragan, Moritz Hardt:
The Social Cost of Strategic Classification. CoRR abs/1808.08460 (2018) - [i18]Allan Zhou, Anca D. Dragan:
Cost Functions for Robot Motion Style. CoRR abs/1809.00092 (2018) - [i17]Andreea Bobu, Andrea Bajcsy, Jaime F. Fisac, Anca D. Dragan:
Learning under Misspecified Objective Spaces. CoRR abs/1810.05157 (2018) - [i16]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) - [i15]Minae Kwon, Sandy H. Huang, Anca D. Dragan:
Expressing Robot Incapability. CoRR abs/1810.08167 (2018) - [i14]Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan:
Establishing Appropriate Trust via Critical States. CoRR abs/1810.08174 (2018) - [i13]Andrea Bajcsy, Sylvia L. Herbert, David Fridovich-Keil, Jaime F. Fisac, Sampada Deglurkar, Anca D. Dragan, Claire J. Tomlin:
A Scalable Framework For Real-Time Multi-Robot, Multi-Human Collision Avoidance. CoRR abs/1811.05929 (2018) - [i12]Jason Y. Zhang, Anca D. Dragan:
Learning from Intended Corrections. CoRR abs/1812.01225 (2018) - [i11]Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan:
Human-AI Learning Performance in Multi-Armed Bandits. CoRR abs/1812.09376 (2018) - 2017
- [c44]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
The Off-Switch Game. AAAI Workshops 2017 - [c43]Jacob Andreas, Anca D. Dragan, Dan Klein:
Translating Neuralese. ACL (1) 2017: 232-242 - [c42]Michael Laskey, Jonathan Lee, Roy Fox, Anca D. Dragan, Ken Goldberg:
DART: Noise Injection for Robust Imitation Learning. CoRL 2017: 143-156 - [c41]Andrea Bajcsy, Dylan P. Losey, Marcia K. O'Malley, Anca D. Dragan:
Learning Robot Objectives from Physical Human Interaction. CoRL 2017: 217-226 - [c40]Allan Zhou, Dylan Hadfield-Menell, Anusha Nagabandi, Anca D. Dragan:
Expressive Robot Motion Timing. HRI 2017: 22-31 - [c39]Chandrayee Basu, Qian Yang, David Hungerman, Mukesh Singhal, Anca D. Dragan:
Do You Want Your Autonomous Car To Drive Like You? HRI 2017: 417-425 - [c38]Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Ken Goldberg:
Comparing human-centric and robot-centric sampling for robot deep learning from demonstrations. ICRA 2017: 358-365 - [c37]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
The Off-Switch Game. IJCAI 2017: 220-227 - [c36]Smitha Milli, Dylan Hadfield-Menell, Anca D. Dragan, Stuart Russell:
Should Robots be Obedient? IJCAI 2017: 4754-4760 - [c35]Jaime F. Fisac, Monica A. Gates, Jessica B. Hamrick, Chang Liu, Dylan Hadfield-Menell, Malayandi Palaniappan, Dhruv Malik, S. Shankar Sastry, Thomas L. Griffiths, Anca D. Dragan:
Pragmatic-Pedagogic Value Alignment. ISRR 2017: 49-57 - [c34]Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart J. Russell, Anca D. Dragan:
Inverse Reward Design. NIPS 2017: 6765-6774 - [c33]Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan:
Enabling Robots to Communicate Their Objectives. Robotics: Science and Systems 2017 - [c32]Dorsa Sadigh, Anca D. Dragan, Shankar Sastry, Sanjit A. Seshia:
Active Preference-Based Learning of Reward Functions. Robotics: Science and Systems 2017 - [i10]Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan:
Enabling Robots to Communicate their Objectives. CoRR abs/1702.03465 (2017) - [i9]Jacob Andreas, Anca D. Dragan, Dan Klein:
Translating Neuralese. CoRR abs/1704.06960 (2017) - [i8]Anca D. Dragan:
Robot Planning with Mathematical Models of Human State and Action. CoRR abs/1705.04226 (2017) - [i7]Smitha Milli, Dylan Hadfield-Menell, Anca D. Dragan, Stuart Russell:
Should Robots be Obedient? CoRR abs/1705.09990 (2017) - [i6]Jaime F. Fisac, Monica A. Gates, Jessica B. Hamrick, Chang Liu, Dylan Hadfield-Menell, Malayandi Palaniappan, Dhruv Malik, S. Shankar Sastry, Thomas L. Griffiths, Anca D. Dragan:
Pragmatic-Pedagogic Value Alignment. CoRR abs/1707.06354 (2017) - [i5]Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart Russell, Anca D. Dragan:
Inverse Reward Design. CoRR abs/1711.02827 (2017) - 2016
- [c31]Chang Liu, Jessica B. Hamrick, Jaime F. Fisac, Anca D. Dragan, J. Karl Hedrick, S. Shankar Sastry, Thomas L. Griffiths:
Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration. AAMAS 2016: 940-948 - [c30]Michael Laskey, Jonathan Lee, Caleb Chuck, David V. Gealy, Wesley Yu-Shu Hsieh, Florian T. Pokorny, Anca D. Dragan, Ken Goldberg:
Robot grasping in clutter: Using a hierarchy of supervisors for learning from demonstrations. CASE 2016: 827-834 - [c29]Negar Mehr, Roberto Horowitz, Anca D. Dragan:
Inferring and assisting with constraints in shared autonomy. CDC 2016: 6689-6696 - [c28]Stefanos Nikolaidis, Anca D. Dragan, Siddhartha S. Srinivasa:
Viewpoint-Based Legibility Optimization. HRI 2016: 271-278 - [c27]Michael Laskey, Sam Staszak, Wesley Yu-Shu Hsieh, Jeffrey Mahler, Florian T. Pokorny, Anca D. Dragan, Ken Goldberg:
SHIV: Reducing supervisor burden in DAgger using support vectors for efficient learning from demonstrations in high dimensional state spaces. ICRA 2016: 462-469 - [c26]Dorsa Sadigh, S. Shankar Sastry, Sanjit A. Seshia, Anca D. Dragan:
Information gathering actions over human internal state. IROS 2016: 66-73 - [c25]Aaron M. Bestick, Ruzena Bajcsy, Anca D. Dragan:
Implicitly Assisting Humans to Choose Good Grasps in Robot to Human Handovers. ISER 2016: 341-354 - [c24]Dylan Hadfield-Menell, Stuart Russell, Pieter Abbeel, Anca D. Dragan:
Cooperative Inverse Reinforcement Learning. NIPS 2016: 3909-3917 - [c23]Zita Marinho, Byron Boots, Anca D. Dragan, Arunkumar Byravan, Geoffrey J. Gordon, Siddhartha S. Srinivasa:
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. Robotics: Science and Systems 2016 - [c22]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 - [c21]Jaime F. Fisac, Chang Liu, Jessica B. Hamrick, Shankar Sastry, J. Karl Hedrick, Thomas L. Griffiths, Anca D. Dragan:
Generating Plans that Predict Themselves. WAFR 2016: 144-159 - [i4]Zita Marinho, Anca D. Dragan, Arunkumar Byravan, Byron Boots, Siddhartha S. Srinivasa, Geoffrey J. Gordon:
Functional Gradient Motion Planning in Reproducing Kernel Hilbert Spaces. CoRR abs/1601.03648 (2016) - [i3]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
Cooperative Inverse Reinforcement Learning. CoRR abs/1606.03137 (2016) - [i2]Michael Laskey, Caleb Chuck, Jonathan Lee, Jeffrey Mahler, Sanjay Krishnan, Kevin G. Jamieson, Anca D. Dragan, Kenneth Y. Goldberg:
Comparing Human-Centric and Robot-Centric Sampling for Robot Deep Learning from Demonstrations. CoRR abs/1610.00850 (2016) - [i1]Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart Russell:
The Off-Switch Game. CoRR abs/1611.08219 (2016) - 2015
- [b1]Anca D. Dragan:
Legible Robot Motion Planning. Carnegie Mellon University, USA, 2015 - [j7]Anca D. Dragan, Rachel M. Holladay, Siddhartha S. Srinivasa:
Deceptive robot motion: synthesis, analysis and experiments. Auton. Robots 39(3): 331-345 (2015) - [c20]Anca D. Dragan, Shira Bauman, Jodi Forlizzi, Siddhartha S. Srinivasa:
Effects of Robot Motion on Human-Robot Collaboration. HRI 2015: 51-58 - [c19]Anca D. Dragan, Katharina Mülling, J. Andrew Bagnell, Siddhartha S. Srinivasa:
Movement primitives via optimization. ICRA 2015: 2339-2346 - [c18]Elizabeth Cha, Anca D. Dragan, Siddhartha S. Srinivasa:
Perceived robot capability. RO-MAN 2015: 541-548 - 2014
- [j6]Anca D. Dragan, Siddhartha S. Srinivasa:
Integrating human observer inferences into robot motion planning. Auton. Robots 37(4): 351-368 (2014) - [c17]Henny Admoni, Anca D. Dragan, Siddhartha S. Srinivasa, Brian Scassellati:
Deliberate delays during robot-to-human handovers improve compliance with gaze communication. HRI 2014: 49-56 - [c16]Elizabeth Cha, Anca D. Dragan, Jodi Forlizzi, Siddhartha S. Srinivasa:
Effects of speech on perceived capability. HRI 2014: 134-135 - [c15]Elizabeth Cha, Anca D. Dragan, Siddhartha S. Srinivasa:
Pre-school children's first encounter with a robot. HRI 2014: 136-137 - [c14]Anca D. Dragan, Siddhartha S. Srinivasa:
Familiarization to robot motion. HRI 2014: 366-373 - [c13]Rachel M. Holladay, Anca D. Dragan, Siddhartha S. Srinivasa:
Legible robot pointing. RO-MAN 2014: 217-223 - [c12]Anca D. Dragan, Rachel M. Holladay, Siddhartha S. Srinivasa:
An Analysis of Deceptive Robot Motion. Robotics: Science and Systems 2014 - 2013
- [j5]Anca D. Dragan, Siddhartha S. Srinivasa:
A policy-blending formalism for shared control. Int. J. Robotics Res. 32(7): 790-805 (2013) - [j4]Matthew Zucker, Nathan D. Ratliff, Anca D. Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher M. Dellin, J. Andrew Bagnell, Siddhartha S. Srinivasa:
CHOMP: Covariant Hamiltonian optimization for motion planning. Int. J. Robotics Res. 32(9-10): 1164-1193 (2013) - [j3]Kyle Strabala, Min Kyung Lee, Anca D. Dragan, Jodi Forlizzi, Siddhartha S. Srinivasa, Maya Cakmak, Vincenzo Micelli:
Toward seamless human-robot handovers. J. Hum. Robot Interact. 2(1): 112-132 (2013) - [j2]Anca D. Dragan, Siddhartha S. Srinivasa, Kenton C. T. Lee:
Teleoperation with intelligent and customizable interfaces. J. Hum. Robot Interact. 2(2): 33-57 (2013) - [c11]Elizabeth Cha, Anca D. Dragan, Siddhartha S. Srinivasa:
Effects of robot capability on user acceptance. HRI 2013: 97-98 - [c10]Kenton C. T. Lee, Anca D. Dragan, Siddhartha S. Srinivasa:
Legible user input for intent prediction. HRI 2013: 175-176 - [c9]Anca D. Dragan, Kenton C. T. Lee, Siddhartha S. Srinivasa:
Legibility and predictability of robot motion. HRI 2013: 301-308 - [c8]Anca D. Dragan, Andrea Lockerd Thomaz, Siddhartha S. Srinivasa:
Collaborative manipulation: new challenges for robotics and HRI. HRI 2013: 435-436 - [c7]Anca D. Dragan, Siddhartha S. Srinivasa:
Generating Legible Motion. Robotics: Science and Systems 2013 - 2012
- [j1]Siddhartha S. Srinivasa, Dmitry Berenson, Maya Cakmak, Alvaro Collet, Mehmet Remzi Dogar, Anca D. Dragan, Ross A. Knepper, Tim Niemueller, Kyle Strabala, Michael Vande Weghe, Julius Ziegler:
Herb 2.0: Lessons Learned From Developing a Mobile Manipulator for the Home. Proc. IEEE 100(8): 2410-2428 (2012) - [c6]Anca D. Dragan, Siddhartha S. Srinivasa:
Assistive teleoperation for manipulation tasks. HRI 2012: 123-124 - [c5]Anca D. Dragan, Siddhartha S. Srinivasa:
Online customization of teleoperation interfaces. RO-MAN 2012: 919-924 - [c4]Kyle Strabala, Min Kyung Lee, Anca D. Dragan, Jodi Forlizzi, Siddhartha S. Srinivasa:
Learning the communication of intent prior to physical collaboration. RO-MAN 2012: 968-973 - [c3]Anca D. Dragan, Siddhartha S. Srinivasa:
Formalizing Assistive Teleoperation. Robotics: Science and Systems 2012 - 2011
- [c2]Anca D. Dragan, Nathan D. Ratliff, Siddhartha S. Srinivasa:
Manipulation planning with goal sets using constrained trajectory optimization. ICRA 2011: 4582-4588 - [c1]Anca D. Dragan, Geoffrey J. Gordon, Siddhartha S. Srinivasa:
Learning from Experience in Manipulation Planning: Setting the Right Goals. ISRR 2011: 309-326
Coauthor Index
Micah Carroll
aka: Micah D. Carroll
aka: Micah D. Carroll
Jaime Fernández Fisac
aka: Jaime F. Fisac
aka: Jaime F. Fisac
Stuart Russell 0001
aka: Stuart J. Russell
aka: Stuart J. Russell
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