| 2025 | ICLR | Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. | Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum |
| 2025 | ICLR | An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. | Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang |
| 2024 | AAAI | Learning Optimal Advantage from Preferences and Mistaking It for Reward. | W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum |
| 2024 | CoRL | A Dual Approach to Imitation Learning from Observations with Offline Datasets. | Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum |
| 2024 | ICLR | Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. | Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh |
| 2024 | ICLR | Score Models for Offline Goal-Conditioned Reinforcement Learning. | Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum |
| 2024 | ICLR | Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. | Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum |
| 2023 | AAAI | The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. | Serena Booth, W. Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, Alessandro Allievi |
| 2022 | ICLR | Fairness Guarantees under Demographic Shift. | Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum |
| 2022 | IROS | Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots. | Akanksha Saran, Kush Desai, Mai Lee Chang, Rudolf Lioutikov, Andrea Thomaz, Scott Niekum |
| 2021 | AAAI | Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback. | Yuchen Cui, Qiping Zhang, Sahil Jain, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox |
| 2021 | CoRL | You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL. | Wonjoon Goo, Scott Niekum |
| 2021 | CoRL | Distributional Depth-Based Estimation of Object Articulation Models. | Ajinkya Jain, Stephen Giguere, Rudolf Lioutikov, Scott Niekum |
| 2021 | CoRL | SCAPE: Learning Stiffness Control from Augmented Position Control Experiences. | Mincheol Kim, Scott Niekum, Ashish D. Deshpande |
| 2021 | ICML | Value Alignment Verification. | Daniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum |
| 2021 | IJCAI | Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning. | Yuchen Cui, Pallavi Koppol, Henny Admoni, Scott Niekum, Reid G. Simmons, Aaron Steinfeld, Tesca Fitzgerald |
| 2021 | ICRA | ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory. | Ajinkya Jain, Rudolf Lioutikov, Caleb Chuck, Scott Niekum |
| 2021 | IROS | Self-Supervised Online Reward Shaping in Sparse-Reward Environments. | Farzan Memarian, Wonjoon Goo, Rudolf Lioutikov, Scott Niekum, Ufuk Topcu |
| 2020 | CoRL | The EMPATHIC Framework for Task Learning from Implicit Human Feedback. | Yuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum |
| 2020 | CoRL | PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards. | Prasoon Goyal, Scott Niekum, Raymond J. Mooney |
| 2020 | ICML | Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences. | Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum |
| 2020 | IJCAI | Human Gaze Assisted Artificial Intelligence: A Review. | Ruohan Zhang, Akanksha Saran, Bo Liu, Yifeng Zhu, Sihang Guo, Scott Niekum, Dana H. Ballard, Mary M. Hayhoe |
| 2020 | IROS | Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. | Caleb Chuck, Supawit Chockchowwat, Scott Niekum |
| 2020 | IROS | Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty. | Ajinkya Jain, Scott Niekum |
| 2019 | AAAI | Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications. | Daniel S. Brown, Scott Niekum |
| 2019 | CoRL | Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations. | Daniel S. Brown, Wonjoon Goo, Scott Niekum |
| 2019 | CoRL | Understanding Teacher Gaze Patterns for Robot Learning. | Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum |
| 2019 | HRI | Learning from Corrective Demonstrations. | Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz |
| 2019 | HRI | Enhancing Robot Learning with Human Social Cues. | Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum |
| 2019 | ICML | Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. | Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum |
| 2019 | ICML | Importance Sampling Policy Evaluation with an Estimated Behavior Policy. | Josiah Hanna, Scott Niekum, Peter Stone |
| 2019 | IJCAI | Using Natural Language for Reward Shaping in Reinforcement Learning. | Prasoon Goyal, Scott Niekum, Raymond J. Mooney |
| 2019 | ICRA | Uncertainty-Aware Data Aggregation for Deep Imitation Learning. | Yuchen Cui, David Isele, Scott Niekum, Kikuo Fujimura |
| 2019 | ICRA | One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video. | Wonjoon Goo, Scott Niekum |
| 2018 | AAAI | Safe Reinforcement Learning via Shielding. | Mohammed Alshiekh, Roderick Bloem, Rdiger Ehlers, Bettina Knighofer, Scott Niekum, Ufuk Topcu |
| 2018 | AAAI | Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning. | Daniel S. Brown, Scott Niekum |
| 2018 | CoRL | Risk-Aware Active Inverse Reinforcement Learning. | Daniel S. Brown, Yuchen Cui, Scott Niekum |
| 2018 | CoRL | Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics. | Ajinkya Jain, Scott Niekum |
| 2018 | HRI | Asking for Help Effectively via Modeling of Human Beliefs. | Taylor Kessler Faulkner, Scott Niekum, Andrea Thomaz |
| 2018 | ICRA | Active Reward Learning from Critiques. | Yuchen Cui, Scott Niekum |
| 2018 | ICRA | Incremental Task Modification via Corrective Demonstrations. | Reymundo A. Gutierrez, Vivian Chu, Andrea Lockerd Thomaz, Scott Niekum |
| 2018 | IROS | Human Gaze Following for Human-Robot Interaction. | Akanksha Saran, Srinjoy Majumdar, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum |
| 2017 | AAAI | Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. | Josiah P. Hanna, Peter Stone, Scott Niekum |
| 2017 | ICML | Data-Efficient Policy Evaluation Through Behavior Policy Search. | Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum |
| 2017 | IROS | Classification error correction: A case study in brain-computer interfacing. | Hasan A. Poonawala, Mohammed Alshiekh, Scott Niekum, Ufuk Topcu |
| 2017 | IROS | Viewpoint selection for visual failure detection. | Akanksha Saran, Branka Lakic, Srinjoy Majumdar, Jrgen Hess, Scott Niekum |
| 2016 | ICML | On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. | Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone |
| 2015 | ICRA | Active articulation model estimation through interactive perception. | Karol Hausman, Scott Niekum, Sarah Osentoski, Gaurav S. Sukhatme |
| 2015 | ICRA | Online Bayesian changepoint detection for articulated motion models. | Scott Niekum, Sarah Osentoski, Christopher G. Atkeson, Andrew G. Barto |
| 2012 | AAAI | Complex Task Learning from Unstructured Demonstrations. | Scott Niekum |
| 2012 | IROS | Learning and generalization of complex tasks from unstructured demonstrations. | Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Andrew G. Barto |
| 2011 | AAAI | Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. | Scott Niekum, Andrew G. Barto |
| 2011 | GECCO | Evolution of reward functions for reinforcement learning. | Scott Niekum, Lee Spector, Andrew G. Barto |
| 2010 | AAAI | Evolved Intrinsic Reward Functions for Reinforcement Learning. | Scott Niekum |