Publications
Optimizing Robot Behavior via Comparative Language Feedback Jeremy Tien*, Zhaojing Yang*, Miru Jun, Stuart J. Russell, Anca Dragan, Erdem Bıyık 3rd Workshop on Human-Interactive Robot Learning (HIRL) at ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2024 * denotes equal contribution. |
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DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning Anthony Liang, Guy Tennenholtz, Chih-wei Hsu, Yinlam Chow, Erdem Bıyık, Craig Boutilier arXiv preprint, February 2024 |
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Batch Active Learning of Reward Functions from Human Preferences Erdem Bıyık, Nima Anari, Dorsa Sadigh ACM Transactions on Human-Robot Interaction (THRI), 2024 |
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RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback Yufei Wang, Zhanyi Sun, Jesse Zhang, Zhou Xian, Erdem Bıyık, David Held, Zackory Erickson arXiv preprint, February 2024 |
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A Generalized Acquisition Function for Preference-based Reward Learning Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca Dragan, Erdem Bıyık International Conference on Robotics and Automation (ICRA), May 2024 |
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Active Preference-Based Gaussian Process Regression for Reward Learning and Optimization Erdem Bıyık, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh International Journal of Robotics Research (IJRR), 2024 |
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Preference Elicitation with Soft Attributes in Interactive Recommendation Erdem Bıyık, Fan Yao, Yinlam Chow, Alex Haig, Chih-wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier arXiv preprint, November 2023 |
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RoboCLIP: One Demonstration is Enough to Learn Robot Policies Sumedh A. Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Bıyık, Dorsa Sadigh, Chelsea Finn, Laurent Itti Conference on Neural Information Processing Systems (NeurIPS), December 2023 |
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Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback Stephen Casper*, Xander Davies*, et al. Transactions on Machine Learning Research (TMLR), 2023 * denotes equal contribution. |
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Active Reward Learning from Online Preferences Vivek Myers, Erdem Bıyık, Dorsa Sadigh International Conference on Robotics and Automation (ICRA), May 2023 |
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ViSaRL: Visual Reinforcement Learning Guided by Human Saliency Anthony Liang, Jesse Thomason, Erdem Bıyık Pretraining for Robotics Workshop at ICRA, May 2023 Oral presentation. |
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Assistive Teaching of Motor Control Tasks to Humans Megha Srivastava, Erdem Bıyık, Suvir Mirchandani, Noah Goodman, Dorsa Sadigh Conference on Neural Information Processing Systems (NeurIPS), November 2022 |
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How do People Incorporate Advice from Artificial Agents when Making Physical Judgments? Erik Brockbank*, Haoliang Wang*, Justin Yang, Suvir Mirchandani, Erdem Bıyık, Dorsa Sadigh, Judith Fan Cognitive Science Society Conference (CogSci), July 2022 * denotes equal contribution. Oral presentation. |
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Learning Preferences For Interactive Autonomy Erdem Bıyık EE Department, Stanford University, May 2022 Ph.D. Dissertation |
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Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction Zhangjie Cao, Erdem Bıyık, Guy Rosman, Dorsa Sadigh International Conference on Robotics and Automation (ICRA), May 2022 |
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APReL: A Library for Active Preference-based Reward Learning Algorithms Erdem Bıyık, Aditi Talati, Dorsa Sadigh 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2022 Also presented at Artificial Intelligence for Human-Robot Interaction (AI-HRI) at AAAI Fall Symposium Series, November 2021 (PDF). |
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Learning from Humans for Adaptive Interaction Erdem Bıyık The 17th Annual Human-Robot Interaction Pioneers Workshop (HRI Pioneers), March 2022 |
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Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams Erdem Bıyık, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh Proceedings of the 36th AAAI Conference on Artificial Intelligence, February 2022 Also presented at Artificial Intelligence for Human-Robot Interaction (AI-HRI) at AAAI Fall Symposium Series, November 2021 (PDF). Oral presentation. |
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Learning Multimodal Rewards from Rankings Vivek Myers, Erdem Bıyık, Nima Anari, Dorsa Sadigh Proceedings of the 5th Conference on Robot Learning (CoRL), November 2021 Oral presentation. |
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Learning Reward Functions from Scale Feedback Nils Wilde*, Erdem Bıyık*, Dorsa Sadigh, Stephen L. Smith Proceedings of the 5th Conference on Robot Learning (CoRL), November 2021 * denotes equal contribution. |
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Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences Erdem Bıyık, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh The International Journal of Robotics Research (IJRR), 2021 |
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Learning How to Dynamically Route Autonomous Vehicles on Shared Roads Daniel A. Lazar*, Erdem Bıyık*, Dorsa Sadigh, Ramtin Pedarsani Transportation Research Part C: Emerging Technologies (TR_C), September 2021 * denotes equal contribution. |
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Emergent Prosociality in Multi-Agent Games Through Gifting Woodrow Z. Wang*, Mark Beliaev*, Erdem Bıyık*, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh 30th International Joint Conference on Artificial Intelligence (IJCAI), August 2021 * denotes equal contribution. |
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Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy Erdem Bıyık*, Daniel A. Lazar*, Ramtin Pedarsani, Dorsa Sadigh IEEE Transactions on Control of Network Systems (TCNS), 2021 * denotes equal contribution. |
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ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes Kejun Li, Maegan Tucker, Erdem Bıyık, Ellen Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames International Conference on Robotics and Automation (ICRA), May 2021 |
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Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic Mark Beliaev, Erdem Bıyık, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani 12th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), May 2021 |
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Multi-Agent Safe Planning with Gaussian Processes Zheqing Zhu, Erdem Bıyık, Dorsa Sadigh Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2020 |
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Active Preference-Based Gaussian Process Regression for Reward Learning Erdem Bıyık*, Nicolas Huynh*, Mykel J. Kochenderfer, Dorsa Sadigh Proceedings of Robotics: Science and Systems (RSS), July 2020 * denotes equal contribution. |
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Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving Zhangjie Cao*, Erdem Bıyık*, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh Proceedings of Robotics: Science and Systems (RSS), July 2020 * denotes equal contribution. |
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Emergent Correlated Equilibrium through Synchronized Exploration Mark Beliaev*, Woodrow Z. Wang*, Daniel A. Lazar, Erdem Bıyık, Dorsa Sadigh, Ramtin Pedarsani RSS 2020 Workshop on Emergent Behaviors in Human-Robot Systems, July 2020 |
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When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans Minae Kwon, Erdem Bıyık, Aditi Talati, Karan Bhasin, Dylan P. Losey, Dorsa Sadigh ACM/IEEE International Conference on Human-Robot Interaction (HRI), March 2020 Also presented at Cooperative AI NeurIPS Workshop 2021, December 2021 (PDF). Honorable mention award. |
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The Green Choice: Learning and Influencing Human Decisions on Shared Roads Erdem Bıyık, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani Proceedings of the 58th IEEE Conference on Decision and Control (CDC), December 2019 |
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Active Learning of Reward Dynamics from Hierarchical Queries Chandrayee Basu, Erdem Bıyık, Zhixun He, Mukesh Singhal, Dorsa Sadigh Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), November 2019 |
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Asking Easy Questions: A User-Friendly Approach to Active Reward Learning Erdem Bıyık, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh Proceedings of the 3rd Conference on Robot Learning (CoRL), October 2019 |
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Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models Erdem Bıyık*, Jonathan Margoliash*, Shahrouz R. Alimo, Dorsa Sadigh Proceedings of the American Control Conference (ACC), July 2019 * denotes equal contribution. |
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Batch Active Learning Using Determinantal Point Processes Erdem Bıyık, Kenneth Wang, Nima Anari, Dorsa Sadigh arXiv preprint, June 2019 |
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Altruistic Autonomy: Beating Congestion on Shared Roads Erdem Bıyık*, Daniel A. Lazar*, Ramtin Pedarsani, Dorsa Sadigh Proceedings of the 13th International Workshop on Algorithmic Foundations of Robotics (WAFR), December 2018 * denotes equal contribution. |
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Batch Active Preference-Based Learning of Reward Functions Erdem Bıyık, Dorsa Sadigh Proceedings of the 2nd Conference on Robot Learning (CoRL), October 2018 Oral presentation. |
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Real-Time Detection, Tracking and Classification of Multiple Moving Objects in UAV Videos Hüseyin C. Baykara*, Erdem Bıyık*, Gamze Gül*, Deniz Onural*, Ahmet S. Öztürk*, İlkay Yıldız* International Conference on Tools with Artificial Intelligence (ICTAI), November 2017 * denotes equal contribution. |
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