Scott Niekum

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 115

Top Venues

CoRR

CoRL

IROS

AAAI

Publications

Prasann Singhal, Nathan Lambert, Scott Niekum, Tanya Goyal, Greg Durrett
D2PO: Discriminator-Guided DPO with Response Evaluation Models. CoRR (2024)
Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
A Dual Approach to Imitation Learning from Observations with Offline Datasets. CoRR (2024)
W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Gabriele Allievi
Models of human preference for learning reward functions. Trans. Mach. Learn. Res. 2024 (2024)
Caleb Chuck, Carl Qi, Michael J. Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi, Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan Mehta, Anthony Wang, Peter Stone, Amy Zhang, Scott Niekum
Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. CoRR (2024)
Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi
Gaze Supervision for Mitigating Causal Confusion in Driving Agents. IV (2024)
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)
Ryan Boldi, Li Ding, Lee Spector, Scott Niekum
Pareto-Optimal Learning from Preferences with Hidden Context. CoRR (2024)
Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
Learning Action-based Representations Using Invariance. CoRR (2024)
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)
Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
Score Models for Offline Goal-Conditioned Reinforcement Learning. ICLR (2024)
Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum
Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. ICLR (2024)
Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi
Gaze Supervision for Mitigating Causal Confusion in Driving Agents. AAMAS (2024)
Rafael Rafailov, Yaswanth Chittepu, Ryan Park, Harshit Sikchi, Joey Hejna, W. Bradley Knox, Chelsea Finn, Scott Niekum
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. CoRR (2024)
Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum
Granger Causal Interaction Skill Chains. Trans. Mach. Learn. Res. 2024 (2024)
Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere, Amy Zhang, David Jensen, Scott Niekum
Automated Discovery of Functional Actual Causes in Complex Environments. CoRR (2024)
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 (2023)
Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
Score Models for Offline Goal-Conditioned Reinforcement Learning. CoRR (2023)
Harshit Sikchi, Amy Zhang, Scott Niekum
Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods. CoRR (2023)
Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum
Granger-Causal Hierarchical Skill Discovery. CoRR (2023)
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 (2023)
Serena Booth, W. Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, Alessandro Allievi
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. AAAI (2023)
Harshit Sikchi, Akanksha Saran, Wonjoon Goo, Scott Niekum
A Ranking Game for Imitation Learning. Trans. Mach. Learn. Res. 2023 (2023)
Andrew Levy, Sreehari Rammohan, Alessandro Allievi, Scott Niekum, George Konidaris
Hierarchical Empowerment: Towards Tractable Empowerment-Based Skill-Learning. CoRR (2023)
Prasoon Goyal, Raymond J. Mooney, Scott Niekum
Language-guided Task Adaptation for Imitation Learning. CoRR (2023)
W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Allievi
Models of human preference for learning reward functions. CoRR (2022)
Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran
Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? CoRR (2022)
Akanksha Saran, Kush Desai, Mai Lee Chang, Rudolf Lioutikov, Andrea Thomaz, Scott Niekum
Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots. IROS (2022)
Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran
Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? L4DC (2022)
Harshit Sikchi, Akanksha Saran, Wonjoon Goo, Scott Niekum
A Ranking Game for Imitation Learning. CoRR (2022)
Akanksha Saran, Kush Desai, Mai Lee Chang, Rudolf Lioutikov, Andrea Thomaz, Scott Niekum
Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots. CoRR (2022)
Wonjoon Goo, Scott Niekum
Know Your Boundaries: The Necessity of Explicit Behavioral Cloning in Offline RL. CoRR (2022)
Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum
Fairness Guarantees under Demographic Shift. ICLR (2022)
Farzan Memarian, Wonjoon Goo, Rudolf Lioutikov, Ufuk Topcu, Scott Niekum
Self-Supervised Online Reward Shaping in Sparse-Reward Environments. CoRR (2021)
Farzan Memarian, Wonjoon Goo, Rudolf Lioutikov, Scott Niekum, Ufuk Topcu
Self-Supervised Online Reward Shaping in Sparse-Reward Environments. IROS (2021)
Christina J. Yuan, Yash Chandak, Stephen Giguere, Philip S. Thomas, Scott Niekum
SOPE: Spectrum of Off-Policy Estimators. CoRR (2021)
Ajinkya Jain, Stephen Giguere, Rudolf Lioutikov, Scott Niekum
Distributional Depth-Based Estimation of Object Articulation Models. CoRL (2021)
Josiah P. Hanna, Scott Niekum, Peter Stone
Importance sampling in reinforcement learning with an estimated behavior policy. Mach. Learn. 110 (6) (2021)
Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
Universal Off-Policy Evaluation. CoRR (2021)
Daniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum
Value Alignment Verification. ICML (2021)
Christina J. Yuan, Yash Chandak, Stephen Giguere, Philip S. Thomas, Scott Niekum
SOPE: Spectrum of Off-Policy Estimators. NeurIPS (2021)
Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone
Adversarial Intrinsic Motivation for Reinforcement Learning. CoRR (2021)
Wonjoon Goo, Scott Niekum
You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL. CoRL (2021)
Wonjoon Goo, Scott Niekum
You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL. CoRR (2021)
Yuchen Cui, Pallavi Koppol, Henny Admoni, Scott Niekum, Reid G. Simmons, Aaron Steinfeld, Tesca Fitzgerald
Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning. IJCAI (2021)
Oliver Kroemer, Scott Niekum, George Konidaris
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms. J. Mach. Learn. Res. 22 (2021)
Ajinkya Jain, Rudolf Lioutikov, Caleb Chuck, Scott Niekum
ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory. ICRA (2021)
Yuchen Cui, Qiping Zhang, Sahil Jain, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox
Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback. AAAI (2021)
Prasoon Goyal, Raymond J. Mooney, Scott Niekum
Zero-shot Task Adaptation using Natural Language. CoRR (2021)
Mincheol Kim, Scott Niekum, Ashish D. Deshpande
SCAPE: Learning Stiffness Control from Augmented Position Control Experiences. CoRR (2021)
Mincheol Kim, Scott Niekum, Ashish D. Deshpande
SCAPE: Learning Stiffness Control from Augmented Position Control Experiences. CoRL (2021)
Akanksha Saran, Ruohan Zhang, Elaine Schaertl Short, Scott Niekum
Efficiently Guiding Imitation Learning Agents with Human Gaze. AAMAS (2021)
Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
Universal Off-Policy Evaluation. NeurIPS (2021)
Farzan Memarian, Abolfazl Hashemi, Scott Niekum, Ufuk Topcu
Robust Generative Adversarial Imitation Learning via Local Lipschitzness. CoRR (2021)
Ajinkya Jain, Stephen Giguere, Rudolf Lioutikov, Scott Niekum
Distributional Depth-Based Estimation of Object Articulation Models. CoRR (2021)
Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone
Adversarial Intrinsic Motivation for Reinforcement Learning. NeurIPS (2021)
Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox
The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRR (2020)
Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences. ICML (2020)
Akanksha Saran, Ruohan Zhang, Elaine Schaertl Short, Scott Niekum
Efficiently Guiding Imitation Learning Algorithms with Human Gaze. CoRR (2020)
Daniel S. Brown, Jordan Schneider, Scott Niekum
Value Alignment Verification. CoRR (2020)
Ruohan Zhang, Akanksha Saran, Bo Liu, Yifeng Zhu, Sihang Guo, Scott Niekum, Dana H. Ballard, Mary M. Hayhoe
Human Gaze Assisted Artificial Intelligence: A Review. IJCAI (2020)
Ajinkya Jain, Scott Niekum
Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty. IROS (2020)
Daniel S. Brown, Scott Niekum, Marek Petrik
Bayesian Robust Optimization for Imitation Learning. CoRR (2020)
Daniel S. Brown, Scott Niekum, Marek Petrik
Bayesian Robust Optimization for Imitation Learning. NeurIPS (2020)
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards. CoRR (2020)
Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences. CoRR (2020)
Yuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum
The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRL (2020)
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards. CoRL (2020)
Wonjoon Goo, Scott Niekum
Local Nonparametric Meta-Learning. CoRR (2020)
Caleb Chuck, Supawit Chockchowwat, Scott Niekum
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. IROS (2020)
Ajinkya Jain, Rudolf Lioutikov, Scott Niekum
ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory. CoRR (2020)
Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
Understanding Teacher Gaze Patterns for Robot Learning. CoRR (2019)
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
Using Natural Language for Reward Shaping in Reinforcement Learning. IJCAI (2019)
Wonjoon Goo, Scott Niekum
One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video. ICRA (2019)
Daniel S. Brown, Scott Niekum
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications. AAAI (2019)
Oliver Kroemer, Scott Niekum, George Dimitri Konidaris
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms. CoRR (2019)
Yuchen Cui, David Isele, Scott Niekum, Kikuo Fujimura
Uncertainty-Aware Data Aggregation for Deep Imitation Learning. ICRA (2019)
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
Using Natural Language for Reward Shaping in Reinforcement Learning. CoRR (2019)
Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz
Learning from Corrective Demonstrations. HRI (2019)
Josiah Hanna, Scott Niekum, Peter Stone
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. ICML (2019)
Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
Understanding Teacher Gaze Patterns for Robot Learning. CoRL (2019)
Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
Enhancing Robot Learning with Human Social Cues. HRI (2019)
Yuchen Cui, David Isele, Scott Niekum, Kikuo Fujimura
Uncertainty-Aware Data Aggregation for Deep Imitation Learning. CoRR (2019)
Daniel S. Brown, Yuchen Cui, Scott Niekum
Risk-Aware Active Inverse Reinforcement Learning. CoRR (2019)
Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. ICML (2019)
Daniel S. Brown, Wonjoon Goo, Scott Niekum
Ranking-Based Reward Extrapolation without Rankings. CoRR (2019)
Caleb Chuck, Supawit Chockchowwat, Scott Niekum
Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. CoRR (2019)
Ajinkya Jain, Scott Niekum
Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty. CoRR (2019)
Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. CoRR (2019)
Daniel S. Brown, Scott Niekum
Deep Bayesian Reward Learning from Preferences. CoRR (2019)
Daniel S. Brown, Wonjoon Goo, Scott Niekum
Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations. CoRL (2019)
Daniel S. Brown, Yuchen Cui, Scott Niekum
Risk-Aware Active Inverse Reinforcement Learning. CoRL (2018)
Daniel S. Brown, Scott Niekum
Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning. AAAI (2018)
Ajinkya Jain, Scott Niekum
Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics. CoRL (2018)
Taylor Kessler Faulkner, Scott Niekum, Andrea Thomaz
Asking for Help Effectively via Modeling of Human Beliefs. HRI (Companion) (2018)
Yuqian Jiang, Nick Walker, Minkyu Kim, Nicolas Brissonneau, Daniel S. Brown, Justin W. Hart, Scott Niekum, Luis Sentis, Peter Stone
LAAIR: A Layered Architecture for Autonomous Interactive Robots. CoRR (2018)
Josiah Hanna, Scott Niekum, Peter Stone
Importance Sampling Policy Evaluation with an Estimated Behavior Policy. CoRR (2018)
Mohammed Alshiekh, Roderick Bloem, Rüdiger Ehlers, Bettina Könighofer, Scott Niekum, Ufuk Topcu
Safe Reinforcement Learning via Shielding. AAAI (2018)
Wonjoon Goo, Scott Niekum
Learning Multi-Step Robotic Tasks from Observation. CoRR (2018)
Reymundo A. Gutierrez, Vivian Chu, Andrea Lockerd Thomaz, Scott Niekum
Incremental Task Modification via Corrective Demonstrations. ICRA (2018)
Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz
Towards Online Learning from Corrective Demonstrations. CoRR (2018)

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Publication Activity (10 Years)

Top Topics

Top Venues

Scott Niekum