Publications

DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
Anthony Liang, Guy Tennenholtz, Chih-wei Hsu, Yinlam Chow, Erdem Bıyık, Craig Boutilier
Conference on Neural Information Processing Systems (NeurIPS), December 2024
Trajectory Improvement and Reward Learning from Comparative Language Feedback
Zhaojing Yang, Miru Jun, Jeremy Tien, Stuart J. Russell, Anca Dragan, Erdem Bıyık
Proceedings of the 8th Conference on Robot Learning (CoRL), November 2024

Also presented at HRI Human-Interactive Robot Learning Workshop, March 2024 (PDF).
EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data
Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Bıyık, Joseph J Lim, Yao Liu, Rasool Fakoor
Proceedings of the 8th Conference on Robot Learning (CoRL), November 2024
Accurate and Data-Efficient Toxicity Prediction when Annotators Disagree
Harbani Jaggi*, Kashyap Murali*, Eve Fleisig, Erdem Bıyık
Conference on Empirical Methods in Natural Language Processing (EMNLP), November 2024

* denotes equal contribution.
ViSaRL: Visual Reinforcement Learning Guided by Human Saliency
Anthony Liang, Jesse Thomason, Erdem Bıyık
International Conference on Intelligent Robots and Systems (IROS), October 2024

Also presented at ICRA Pretraining for Robotics Workshop, May 2023 (PDF).
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†
International Conference on Machine Learning (ICML), July 2024

* denotes equal contribution. † denotes equal advising.
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation
Michelle Pan*, Mariah Schrum*, Vivek Myers, Erdem Bıyık, Anca Dragan
International Conference on Machine Learning (ICML), July 2024

* denotes equal contribution.
Foundation Models for Embodied AI
Sumedh Anand Sontakke
CS Department, University of Southern California, May 2024

Ph.D. Dissertation
Batch Active Learning of Reward Functions from Human Preferences
Erdem Bıyık, Nima Anari, Dorsa Sadigh
ACM Transactions on Human-Robot Interaction (THRI), 2024
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
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
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
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
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.
Active Reward Learning from Online Preferences
Vivek Myers, Erdem Bıyık, Dorsa Sadigh
International Conference on Robotics and Automation (ICRA), May 2023
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
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.
Learning Preferences For Interactive Autonomy
Erdem Bıyık
EE Department, Stanford University, May 2022

Ph.D. Dissertation
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
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).
Learning from Humans for Adaptive Interaction
Erdem Bıyık
The 17th Annual Human-Robot Interaction Pioneers Workshop (HRI Pioneers), March 2022
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.
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.
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.
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
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.
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.
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.
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
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
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
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.
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.
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
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.
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
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
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
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.
Batch Active Learning Using Determinantal Point Processes
Erdem Bıyık, Kenneth Wang, Nima Anari, Dorsa Sadigh
arXiv preprint, June 2019
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.
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.
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.