Scott Niekum - RankMe

154 papers A* 40A 11C 1Misc 10Journal 81Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models. CoRR Pranaya Jajoo, Harshit Sikchi, Siddhant Agarwal, Amy Zhang, Scott Niekum, Martha White
2026	J	`jnl`	Safe RLHF Beyond Expectation: Stochastic Dominance for Universal Spectral Risk Control. CoRR Yaswanth Chittepu, Ativ Joshi, Rajarshi Bhattacharjee, Scott Niekum
2025	J	`jnl`	A Descriptive and Normative Theory of Human Beliefs in RLHF. CoRR Sylee Dandekar, Shripad Deshmukh, Frank Chiu, W. Bradley Knox, Scott Niekum
2025	J	`jnl`	Adaptive Margin RLHF via Preference over Preferences. CoRR Yaswanth Chittepu, Prasann Singhal, Greg Durrett, Scott Niekum
2025	A*	`conf`	An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. ICLR Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang
2025	J	`jnl`	An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning. CoRR Haoran Xu, Shuozhe Li, Harshit Sikchi, Scott Niekum, Amy Zhang
2025	J	`jnl`	DeepFleet: Multi-Agent Foundation Models for Mobile Robots. CoRR Ameya Agaskar, Sriram Siva, William Pickering, Kyle O'Brien, Charles Kekeh, Ang Li, Brianna Gallo Sarker, Alicia Chua, Mayur Nemade, Charun Thattai, Jiaming Di, Isaac Iyengar, Ramya Dharoor, Dino Kirouani, Jimmy Erskine, Tamir Hegazy, Scott Niekum, Usman A. Khan, Federico Pecora, Joseph W. Durham
2025	J	`jnl`	Evaluation-Aware Reinforcement Learning. CoRR Shripad Vilasrao Deshmukh, Will Schwarzer, Scott Niekum
2025	J	`jnl`	Fast Adaptation with Behavioral Foundation Models. CoRR Harshit Sikchi, Andrea Tirinzoni, Ahmed Touati, Yingchen Xu, Anssi Kanervisto, Scott Niekum, Amy Zhang, Alessandro Lazaric, Matteo Pirotta
2025	J	`jnl`	Influencing Humans to Conform to Preference Models for RLHF. CoRR Stephane Hatgis-Kessell, W. Bradley Knox, Serena Booth, Scott Niekum, Peter Stone
2025	A*	`conf`	Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. ICLR Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum
2025	J	`jnl`	Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. CoRR Caleb Chuck, Fan Feng, Carl Qi, Chang Shi, Siddhant Agarwal, Amy Zhang, Scott Niekum
2025	J	`jnl`	Pairwise or Pointwise? Evaluating Feedback Protocols for Bias in LLM-Based Evaluation. CoRR Tuhina Tripathi, Manya Wadhwa, Greg Durrett, Scott Niekum
2025	J	`jnl`	Reinforcement Learning from Human Feedback with High-Confidence Safety Constraints. CoRR Yaswanth Chittepu, Blossom Metevier, Will Schwarzer, Austin Hoag, Scott Niekum, Philip S. Thomas
2025	J	`jnl`	Supervised Reward Inference. CoRR Will Schwarzer, Jordan Schneider, Philip S. Thomas, Scott Niekum
2024	Misc	`conf`	A Dual Approach to Imitation Learning from Observations with Offline Datasets. CoRL Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
2024	J	`jnl`	A Dual Approach to Imitation Learning from Observations with Offline Datasets. CoRR Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum
2024	J	`jnl`	Automated Discovery of Functional Actual Causes in Complex Environments. CoRR Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere, Amy Zhang, David Jensen, Scott Niekum
2024	A*	`conf`	Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning. ICLR Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh
2024	J	`jnl`	D2PO: Discriminator-Guided DPO with Response Evaluation Models. CoRR Prasann Singhal, Nathan Lambert, Scott Niekum, Tanya Goyal, Greg Durrett
2024	J	`jnl`	Data-Efficient Policy Evaluation Through Behavior Policy Search. J. Mach. Learn. Res. Josiah P. Hanna, Yash Chandak, Philip S. Thomas, Martha White, Peter Stone, Scott Niekum
2024	A*	`conf`	Dual RL: Unification and New Methods for Reinforcement and Imitation Learning. ICLR Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum
2024	A	`conf`	Gaze Supervision for Mitigating Causal Confusion in Driving Agents. AAMAS Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi
2024	C	`conf`	Gaze Supervision for Mitigating Causal Confusion in Driving Agents. IV Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi
2024	J	`jnl`	Granger Causal Interaction Skill Chains. Trans. Mach. Learn. Res. Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum
2024	J	`jnl`	Learning Action-based Representations Using Invariance. RLJ Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
2024	J	`jnl`	Learning Action-based Representations Using Invariance. CoRR Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang
2024	A*	`conf`	Learning Optimal Advantage from Preferences and Mistaking It for Reward. AAAI W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum
2024	J	`jnl`	Models of human preference for learning reward functions. Trans. Mach. Learn. Res. W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Gabriele Allievi
2024	J	`jnl`	Pareto-Optimal Learning from Preferences with Hidden Context. CoRR Ryan Boldi, Li Ding, Lee Spector, Scott Niekum
2024	A*	`conf`	Predicting Future Actions of Reinforcement Learning Agents. NeurIPS Stephen Chung, Scott Niekum, David Krueger
2024	J	`jnl`	Predicting Future Actions of Reinforcement Learning Agents. CoRR Stephen Chung, Scott Niekum, David Krueger
2024	J	`jnl`	RL Zero: Zero-Shot Language to Behaviors without any Supervision. CoRR Harshit Sikchi, Siddhant Agarwal, Pranaya Jajoo, Samyak Parajuli, Caleb Chuck, Max Rudolph, Peter Stone, Amy Zhang, Scott Niekum
2024	J	`jnl`	Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. CoRR 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
2024	A*	`conf`	Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. NeurIPS Rafael Rafailov, Yaswanth Chittepu, Ryan Park, Harshit Sikchi, Joey Hejna, W. Bradley Knox, Chelsea Finn, Scott Niekum
2024	J	`jnl`	Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms. CoRR Rafael Rafailov, Yaswanth Chittepu, Ryan Park, Harshit Sikchi, Joey Hejna, W. Bradley Knox, Chelsea Finn, Scott Niekum
2024	A*	`conf`	Score Models for Offline Goal-Conditioned Reinforcement Learning. ICLR Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
2024	A*	`conf`	SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. NeurIPS Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone
2024	J	`jnl`	SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions. CoRR Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone
2023	J	`jnl`	A Ranking Game for Imitation Learning. Trans. Mach. Learn. Res. Harshit Sikchi, Akanksha Saran, Wonjoon Goo, Scott Niekum
2023	J	`jnl`	Contrastive Preference Learning: Learning from Human Feedback without RL. CoRR Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh
2023	J	`jnl`	Granger-Causal Hierarchical Skill Discovery. CoRR Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum
2023	J	`jnl`	Hierarchical Empowerment: Towards Tractable Empowerment-Based Skill-Learning. CoRR Andrew Levy, Sreehari Rammohan, Alessandro Allievi, Scott Niekum, George Konidaris
2023	J	`jnl`	Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods. CoRR Harshit Sikchi, Amy Zhang, Scott Niekum
2023	J	`jnl`	Language-guided Task Adaptation for Imitation Learning. CoRR Prasoon Goyal, Raymond J. Mooney, Scott Niekum
2023	J	`jnl`	Learning Optimal Advantage from Preferences and Mistaking it for Reward. CoRR W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur O. Adalgeirsson, Serena Booth, Anca D. Dragan, Peter Stone, Scott Niekum
2023	J	`jnl`	Score Models for Offline Goal-Conditioned Reinforcement Learning. CoRR Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum
2023	A*	`conf`	The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications. AAAI Serena Booth, W. Bradley Knox, Julie Shah, Scott Niekum, Peter Stone, Alessandro Allievi
2022	J	`jnl`	A Ranking Game for Imitation Learning. CoRR Harshit Sikchi, Akanksha Saran, Wonjoon Goo, Scott Niekum
2022	—	`conf`	Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? L4DC Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran
2022	J	`jnl`	Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? CoRR Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran
2022	A*	`conf`	Fairness Guarantees under Demographic Shift. ICLR Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum
2022	J	`jnl`	Know Your Boundaries: The Necessity of Explicit Behavioral Cloning in Offline RL. CoRR Wonjoon Goo, Scott Niekum
2022	J	`jnl`	Models of human preference for learning reward functions. CoRR W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Allievi
2022	A	`conf`	Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots. IROS Akanksha Saran, Kush Desai, Mai Lee Chang, Rudolf Lioutikov, Andrea Thomaz, Scott Niekum
2022	J	`jnl`	Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots. CoRR Akanksha Saran, Kush Desai, Mai Lee Chang, Rudolf Lioutikov, Andrea Thomaz, Scott Niekum
2021	J	`jnl`	A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms. J. Mach. Learn. Res. Oliver Kroemer, Scott Niekum, George Konidaris
2021	A*	`conf`	Adversarial Intrinsic Motivation for Reinforcement Learning. NeurIPS Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone
2021	J	`jnl`	Adversarial Intrinsic Motivation for Reinforcement Learning. CoRR Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone
2021	A*	`conf`	Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback. AAAI Yuchen Cui, Qiping Zhang, Sahil Jain, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox
2021	Misc	`conf`	Distributional Depth-Based Estimation of Object Articulation Models. CoRL Ajinkya Jain, Stephen Giguere, Rudolf Lioutikov, Scott Niekum
2021	J	`jnl`	Distributional Depth-Based Estimation of Object Articulation Models. CoRR Ajinkya Jain, Stephen Giguere, Rudolf Lioutikov, Scott Niekum
2021	A	`conf`	Efficiently Guiding Imitation Learning Agents with Human Gaze. AAMAS Akanksha Saran, Ruohan Zhang, Elaine Schaertl Short, Scott Niekum
2021	J	`jnl`	Importance sampling in reinforcement learning with an estimated behavior policy. Mach. Learn. Josiah P. Hanna, Scott Niekum, Peter Stone
2021	J	`jnl`	Robust Generative Adversarial Imitation Learning via Local Lipschitzness. CoRR Farzan Memarian, Abolfazl Hashemi, Scott Niekum, Ufuk Topcu
2021	Misc	`conf`	SCAPE: Learning Stiffness Control from Augmented Position Control Experiences. CoRL Mincheol Kim, Scott Niekum, Ashish D. Deshpande
2021	J	`jnl`	SCAPE: Learning Stiffness Control from Augmented Position Control Experiences. CoRR Mincheol Kim, Scott Niekum, Ashish D. Deshpande
2021	A*	`conf`	SOPE: Spectrum of Off-Policy Estimators. NeurIPS Christina J. Yuan, Yash Chandak, Stephen Giguere, Philip S. Thomas, Scott Niekum
2021	J	`jnl`	SOPE: Spectrum of Off-Policy Estimators. CoRR Christina J. Yuan, Yash Chandak, Stephen Giguere, Philip S. Thomas, Scott Niekum
2021	A*	`conf`	ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory. ICRA Ajinkya Jain, Rudolf Lioutikov, Caleb Chuck, Scott Niekum
2021	A	`conf`	Self-Supervised Online Reward Shaping in Sparse-Reward Environments. IROS Farzan Memarian, Wonjoon Goo, Rudolf Lioutikov, Scott Niekum, Ufuk Topcu
2021	J	`jnl`	Self-Supervised Online Reward Shaping in Sparse-Reward Environments. CoRR Farzan Memarian, Wonjoon Goo, Rudolf Lioutikov, Ufuk Topcu, Scott Niekum
2021	A*	`conf`	Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning. IJCAI Yuchen Cui, Pallavi Koppol, Henny Admoni, Scott Niekum, Reid G. Simmons, Aaron Steinfeld, Tesca Fitzgerald
2021	A*	`conf`	Universal Off-Policy Evaluation. NeurIPS Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
2021	J	`jnl`	Universal Off-Policy Evaluation. CoRR Yash Chandak, Scott Niekum, Bruno Castro da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas
2021	A*	`conf`	Value Alignment Verification. ICML Daniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum
2021	Misc	`conf`	You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL. CoRL Wonjoon Goo, Scott Niekum
2021	J	`jnl`	You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL. CoRR Wonjoon Goo, Scott Niekum
2021	J	`jnl`	Zero-shot Task Adaptation using Natural Language. CoRR Prasoon Goyal, Raymond J. Mooney, Scott Niekum
2020	A*	`conf`	Bayesian Robust Optimization for Imitation Learning. NeurIPS Daniel S. Brown, Scott Niekum, Marek Petrik
2020	J	`jnl`	Bayesian Robust Optimization for Imitation Learning. CoRR Daniel S. Brown, Scott Niekum, Marek Petrik
2020	J	`jnl`	Efficiently Guiding Imitation Learning Algorithms with Human Gaze. CoRR Akanksha Saran, Ruohan Zhang, Elaine Schaertl Short, Scott Niekum
2020	A*	`conf`	Human Gaze Assisted Artificial Intelligence: A Review. IJCAI Ruohan Zhang, Akanksha Saran, Bo Liu, Yifeng Zhu, Sihang Guo, Scott Niekum, Dana H. Ballard, Mary M. Hayhoe
2020	A	`conf`	Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. IROS Caleb Chuck, Supawit Chockchowwat, Scott Niekum
2020	A	`conf`	Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty. IROS Ajinkya Jain, Scott Niekum
2020	J	`jnl`	Local Nonparametric Meta-Learning. CoRR Wonjoon Goo, Scott Niekum
2020	Misc	`conf`	PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards. CoRL Prasoon Goyal, Scott Niekum, Raymond J. Mooney
2020	J	`jnl`	PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards. CoRR Prasoon Goyal, Scott Niekum, Raymond J. Mooney
2020	A*	`conf`	Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences. ICML Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
2020	J	`jnl`	Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences. CoRR Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum
2020	J	`jnl`	ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory. CoRR Ajinkya Jain, Rudolf Lioutikov, Scott Niekum
2020	Misc	`conf`	The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRL Yuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum
2020	J	`jnl`	The EMPATHIC Framework for Task Learning from Implicit Human Feedback. CoRR Yuchen Cui, Qiping Zhang, Alessandro Allievi, Peter Stone, Scott Niekum, W. Bradley Knox
2020	J	`jnl`	Value Alignment Verification. CoRR Daniel S. Brown, Jordan Schneider, Scott Niekum
2019	J	`jnl`	A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms. CoRR Oliver Kroemer, Scott Niekum, George Dimitri Konidaris
2019	Misc	`conf`	Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations. CoRL Daniel S. Brown, Wonjoon Goo, Scott Niekum
2019	J	`jnl`	Deep Bayesian Reward Learning from Preferences. CoRR Daniel S. Brown, Scott Niekum
2019	A*	`conf`	Enhancing Robot Learning with Human Social Cues. HRI Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
2019	A*	`conf`	Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. ICML Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum
2019	J	`jnl`	Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations. CoRR Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum
2019	J	`jnl`	Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning. CoRR Caleb Chuck, Supawit Chockchowwat, Scott Niekum
2019	A*	`conf`	Importance Sampling Policy Evaluation with an Estimated Behavior Policy. ICML Josiah Hanna, Scott Niekum, Peter Stone
2019	J	`jnl`	Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty. CoRR Ajinkya Jain, Scott Niekum
2019	A*	`conf`	Learning from Corrective Demonstrations. HRI Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz
2019	A*	`conf`	Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications. AAAI Daniel S. Brown, Scott Niekum
2019	A*	`conf`	One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video. ICRA Wonjoon Goo, Scott Niekum
2019	J	`jnl`	Ranking-Based Reward Extrapolation without Rankings. CoRR Daniel S. Brown, Wonjoon Goo, Scott Niekum
2019	J	`jnl`	Risk-Aware Active Inverse Reinforcement Learning. CoRR Daniel S. Brown, Yuchen Cui, Scott Niekum
2019	A*	`conf`	Uncertainty-Aware Data Aggregation for Deep Imitation Learning. ICRA Yuchen Cui, David Isele, Scott Niekum, Kikuo Fujimura
2019	J	`jnl`	Uncertainty-Aware Data Aggregation for Deep Imitation Learning. CoRR Yuchen Cui, David Isele, Scott Niekum, Kikuo Fujimura
2019	Misc	`conf`	Understanding Teacher Gaze Patterns for Robot Learning. CoRL Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
2019	J	`jnl`	Understanding Teacher Gaze Patterns for Robot Learning. CoRR Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
2019	A*	`conf`	Using Natural Language for Reward Shaping in Reinforcement Learning. IJCAI Prasoon Goyal, Scott Niekum, Raymond J. Mooney
2019	J	`jnl`	Using Natural Language for Reward Shaping in Reinforcement Learning. CoRR Prasoon Goyal, Scott Niekum, Raymond J. Mooney
2018	A*	`conf`	Active Reward Learning from Critiques. ICRA Yuchen Cui, Scott Niekum
2018	—	`conf`	Asking for Help Effectively via Modeling of Human Beliefs. HRI (Companion) Taylor Kessler Faulkner, Scott Niekum, Andrea Thomaz
2018	Misc	`conf`	Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics. CoRL Ajinkya Jain, Scott Niekum
2018	J	`jnl`	Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics. CoRR Ajinkya Jain, Scott Niekum
2018	A*	`conf`	Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning. AAAI Daniel S. Brown, Scott Niekum
2018	A	`conf`	Human Gaze Following for Human-Robot Interaction. IROS Akanksha Saran, Srinjoy Majumdar, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum
2018	J	`jnl`	Importance Sampling Policy Evaluation with an Estimated Behavior Policy. CoRR Josiah Hanna, Scott Niekum, Peter Stone
2018	A*	`conf`	Incremental Task Modification via Corrective Demonstrations. ICRA Reymundo A. Gutierrez, Vivian Chu, Andrea Lockerd Thomaz, Scott Niekum
2018	J	`jnl`	LAAIR: A Layered Architecture for Autonomous Interactive Robots. CoRR Yuqian Jiang, Nick Walker, Minkyu Kim, Nicolas Brissonneau, Daniel S. Brown, Justin W. Hart, Scott Niekum, Luis Sentis, Peter Stone
2018	J	`jnl`	Learning Multi-Step Robotic Tasks from Observation. CoRR Wonjoon Goo, Scott Niekum
2018	J	`jnl`	Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications. CoRR Daniel S. Brown, Scott Niekum
2018	Misc	`conf`	Risk-Aware Active Inverse Reinforcement Learning. CoRL Daniel S. Brown, Yuchen Cui, Scott Niekum
2018	A*	`conf`	Safe Reinforcement Learning via Shielding. AAAI Mohammed Alshiekh, Roderick Bloem, Rüdiger Ehlers, Bettina Könighofer, Scott Niekum, Ufuk Topcu
2018	J	`jnl`	Towards Online Learning from Corrective Demonstrations. CoRR Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz
2017	A*	`conf`	Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAAI Josiah P. Hanna, Peter Stone, Scott Niekum
2017	A	`conf`	Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. AAMAS Josiah P. Hanna, Peter Stone, Scott Niekum
2017	A	`conf`	Classification error correction: A case study in brain-computer interfacing. IROS Hasan A. Poonawala, Mohammed Alshiekh, Scott Niekum, Ufuk Topcu
2017	A*	`conf`	Data-Efficient Policy Evaluation Through Behavior Policy Search. ICML Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum
2017	J	`jnl`	Data-Efficient Policy Evaluation Through Behavior Policy Search. CoRR Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum
2017	J	`jnl`	Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning. CoRR Daniel S. Brown, Scott Niekum
2017	J	`jnl`	Safe Reinforcement Learning via Shielding. CoRR Mohammed Alshiekh, Roderick Bloem, Rüdiger Ehlers, Bettina Könighofer, Scott Niekum, Ufuk Topcu
2017	—	`conf`	Toward Probabilistic Safety Bounds for Robot Learning from Demonstration. AAAI Fall Symposia Daniel S. Brown, Scott Niekum
2017	A	`conf`	Viewpoint selection for visual failure detection. IROS Akanksha Saran, Branka Lakic, Srinjoy Majumdar, Jürgen Hess, Scott Niekum
2016	J	`jnl`	High Confidence Off-Policy Evaluation with Models. CoRR Josiah P. Hanna, Peter Stone, Scott Niekum
2016	A*	`conf`	On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. ICML Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone
2015	A*	`conf`	Active articulation model estimation through interactive perception. ICRA Karol Hausman, Scott Niekum, Sarah Osentoski, Gaurav S. Sukhatme
2015	J	`jnl`	Learning grounded finite-state representations from unstructured demonstrations. Int. J. Robotics Res. Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Sachin Chitta, Bhaskara Marthi, Andrew G. Barto
2015	A*	`conf`	Online Bayesian changepoint detection for articulated motion models. ICRA Scott Niekum, Sarah Osentoski, Christopher G. Atkeson, Andrew G. Barto
2015	—	`conf`	Policy Evaluation Using the Ω-Return. NIPS Philip S. Thomas, Scott Niekum, Georgios Theocharous, George Dimitri Konidaris
2014	—	`conf`	Learning pouring skills from demonstration and practice. Humanoids Akihiko Yamaguchi, Christopher G. Atkeson, Scott Niekum, Tsukasa Ogasawara
2013	—	`conf`	An Integrated System for Learning Multi-Step Robotic Tasks from Unstructured Demonstrations. AAAI Spring Symposium: Designing Intelligent Robots Scott Niekum
2013	—	`conf`	Incremental Semantically Grounded Learning from Demonstration. Robotics: Science and Systems Scott Niekum, Sachin Chitta, Andrew G. Barto, Bhaskara Marthi, Sarah Osentoski
2012	A*	`conf`	Complex Task Learning from Unstructured Demonstrations. AAAI Scott Niekum
2012	A	`conf`	Learning and generalization of complex tasks from unstructured demonstrations. IROS Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Andrew G. Barto
2011	—	`conf`	Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. Lifelong Learning Scott Niekum, Andrew G. Barto
2011	—	`conf`	Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. NIPS Scott Niekum, Andrew G. Barto
2011	—	`conf`	Evolution of reward functions for reinforcement learning. GECCO (Companion) Scott Niekum, Lee Spector, Andrew G. Barto
2011	—	`conf`	TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning. NIPS George Dimitri Konidaris, Scott Niekum, Philip S. Thomas
2010	A*	`conf`	Evolved Intrinsic Reward Functions for Reinforcement Learning. AAAI Scott Niekum
2010	J	`jnl`	Genetic Programming for Reward Function Search. IEEE Trans. Auton. Ment. Dev. Scott Niekum, Andrew G. Barto, Lee Spector