Scott Niekum

According to our database, Scott Niekum authored at least 98 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Models of human preference for learning reward functions.

W. Bradley Knox, Stephane Hatgis-Kessell, Serena Booth, Scott Niekum, Peter Stone, Alessandro Gabriele Allievi

Trans. Mach. Learn. Res., 2024

Granger Causal Interaction Skill Chains.

Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum

Trans. Mach. Learn. Res., 2024

Predicting Future Actions of Reinforcement Learning Agents.

Stephen Chung, Scott Niekum, David Krueger

CoRR, 2024

SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions.

Zizhao Wang, Jiaheng Hu, Caleb Chuck, Stephen Chen, Roberto Martín-Martín, Amy Zhang, Scott Niekum, Peter Stone

CoRR, 2024

Pareto-Optimal Learning from Preferences with Hidden Context.

Ryan Boldi, Li Ding, Lee Spector, Scott Niekum

CoRR, 2024

A Dual Approach to Imitation Learning from Observations with Offline Datasets.

Harshit Sikchi, Caleb Chuck, Amy Zhang, Scott Niekum

CoRR, 2024

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms.

Rafael Rafailov, Yaswanth Chittepu, Ryan Park, Harshit Sikchi, Joey Hejna, W. Bradley Knox, Chelsea Finn, Scott Niekum

CoRR, 2024

Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning.

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

CoRR, 2024

D2PO: Discriminator-Guided DPO with Response Evaluation Models.

Prasann Singhal, Nathan Lambert, Scott Niekum, Tanya Goyal, Greg Durrett

CoRR, 2024

Automated Discovery of Functional Actual Causes in Complex Environments.

Caleb Chuck, Sankaran Vaidyanathan, Stephen Giguere, Amy Zhang, David Jensen, Scott Niekum

CoRR, 2024

Learning Action-based Representations Using Invariance.

Max Rudolph, Caleb Chuck, Kevin Black, Misha Lvovsky, Scott Niekum, Amy Zhang

RLJ, 2024

Gaze Supervision for Mitigating Causal Confusion in Driving Agents.

Abhijat Biswas, Badal Arun Pardhi, Caleb Chuck, Jarrett Holtz, Scott Niekum, Henny Admoni, Alessandro Allievi

Proceedings of the IEEE Intelligent Vehicles Symposium, 2024

Dual RL: Unification and New Methods for Reinforcement and Imitation Learning.

Harshit Sikchi, Qinqing Zheng, Amy Zhang, Scott Niekum

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Score Models for Offline Goal-Conditioned Reinforcement Learning.

Harshit Sikchi, Rohan Chitnis, Ahmed Touati, Alborz Geramifard, Amy Zhang, Scott Niekum

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

A Ranking Game for Imitation Learning.

Harshit Sikchi, Akanksha Saran, Wonjoon Goo, Scott Niekum

Trans. Mach. Learn. Res., 2023

Contrastive Preference Learning: Learning from Human Feedback without RL.

Joey Hejna, Rafael Rafailov, Harshit Sikchi, Chelsea Finn, Scott Niekum, W. Bradley Knox, Dorsa Sadigh

CoRR, 2023

Hierarchical Empowerment: Towards Tractable Empowerment-Based Skill-Learning.

Andrew Levy, Sreehari Rammohan, Alessandro Allievi, Scott Niekum, George Konidaris

CoRR, 2023

Granger-Causal Hierarchical Skill Discovery.

Caleb Chuck, Kevin Black, Aditya Arjun, Yuke Zhu, Scott Niekum

CoRR, 2023

Imitation from Arbitrary Experience: A Dual Unification of Reinforcement and Imitation Learning Methods.

Harshit Sikchi, Amy Zhang, Scott Niekum

CoRR, 2023

Language-guided Task Adaptation for Imitation Learning.

Prasoon Goyal, Raymond J. Mooney, Scott Niekum

CoRR, 2023

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

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Know Your Boundaries: The Necessity of Explicit Behavioral Cloning in Offline RL.

Wonjoon Goo, Scott Niekum

CoRR, 2022

Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation?

Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar, Aravind Rajeswaran

Proceedings of the Learning for Dynamics and Control Conference, 2022

Understanding Acoustic Patterns of Human Teachers Demonstrating Manipulation Tasks to Robots.

Akanksha Saran, Kush Desai, Mai Lee Chang, Rudolf Lioutikov, Andrea Thomaz, Scott Niekum

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Fairness Guarantees under Demographic Shift.

Stephen Giguere, Blossom Metevier, Bruno Castro da Silva, Yuriy Brun, Philip S. Thomas, Scott Niekum

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Importance sampling in reinforcement learning with an estimated behavior policy.

Josiah P. Hanna, Scott Niekum, Peter Stone

Mach. Learn., 2021

A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms.

Oliver Kroemer, Scott Niekum, George Konidaris

J. Mach. Learn. Res., 2021

Robust Generative Adversarial Imitation Learning via Local Lipschitzness.

Farzan Memarian, Abolfazl Hashemi, Scott Niekum, Ufuk Topcu

CoRR, 2021

Zero-shot Task Adaptation using Natural Language.

Prasoon Goyal, Raymond J. Mooney, Scott Niekum

CoRR, 2021

SOPE: Spectrum of Off-Policy Estimators.

Christina J. Yuan, Yash Chandak, Stephen Giguere, Philip S. Thomas, Scott Niekum

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adversarial Intrinsic Motivation for Reinforcement Learning.

Ishan Durugkar, Mauricio Tec, Scott Niekum, Peter Stone

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Universal Off-Policy Evaluation.

Yash Chandak, Scott Niekum, Bruno C. da Silva, Erik G. Learned-Miller, Emma Brunskill, Philip S. Thomas

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Self-Supervised Online Reward Shaping in Sparse-Reward Environments.

Farzan Memarian, Wonjoon Goo, Rudolf Lioutikov, Scott Niekum, Ufuk Topcu

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

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

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory.

Ajinkya Jain, Rudolf Lioutikov, Caleb Chuck, Scott Niekum

Proceedings of the IEEE International Conference on Robotics and Automation, 2021

Value Alignment Verification.

Daniel S. Brown, Jordan Schneider, Anca D. Dragan, Scott Niekum

Proceedings of the 38th International Conference on Machine Learning, 2021

SCAPE: Learning Stiffness Control from Augmented Position Control Experiences.

Mincheol Kim, Scott Niekum, Ashish D. Deshpande

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Distributional Depth-Based Estimation of Object Articulation Models.

Ajinkya Jain, Stephen Giguere, Rudolf Lioutikov, Scott Niekum

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL.

Wonjoon Goo, Scott Niekum

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Efficiently Guiding Imitation Learning Agents with Human Gaze.

Akanksha Saran, Ruohan Zhang, Elaine Schaertl Short, Scott Niekum

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Value Alignment Verification.

Daniel S. Brown, Jordan Schneider, Scott Niekum

CoRR, 2020

ScrewNet: Category-Independent Articulation Model Estimation From Depth Images Using Screw Theory.

Ajinkya Jain, Rudolf Lioutikov, Scott Niekum

CoRR, 2020

Efficiently Guiding Imitation Learning Algorithms with Human Gaze.

Akanksha Saran, Ruohan Zhang, Elaine Schaertl Short, Scott Niekum

CoRR, 2020

Local Nonparametric Meta-Learning.

Wonjoon Goo, Scott Niekum

CoRR, 2020

Bayesian Robust Optimization for Imitation Learning.

Daniel S. Brown, Scott Niekum, Marek Petrik

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning Hybrid Object Kinematics for Efficient Hierarchical Planning Under Uncertainty.

Ajinkya Jain, Scott Niekum

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning.

Caleb Chuck, Supawit Chockchowwat, Scott Niekum

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

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

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences.

Daniel S. Brown, Russell Coleman, Ravi Srinivasan, Scott Niekum

Proceedings of the 37th International Conference on Machine Learning, 2020

PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards.

Prasoon Goyal, Scott Niekum, Raymond J. Mooney

Proceedings of the 4th Conference on Robot Learning, 2020

The EMPATHIC Framework for Task Learning from Implicit Human Feedback.

Yuchen Cui, Qiping Zhang, W. Bradley Knox, Alessandro Allievi, Peter Stone, Scott Niekum

Proceedings of the 4th Conference on Robot Learning, 2020

2019

Deep Bayesian Reward Learning from Preferences.

Daniel S. Brown, Scott Niekum

CoRR, 2019

Ranking-Based Reward Extrapolation without Rankings.

Daniel S. Brown, Wonjoon Goo, Scott Niekum

CoRR, 2019

Using Natural Language for Reward Shaping in Reinforcement Learning.

Prasoon Goyal, Scott Niekum, Raymond J. Mooney

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

One-Shot Learning of Multi-Step Tasks from Observation via Activity Localization in Auxiliary Video.

Wonjoon Goo, Scott Niekum

Proceedings of the International Conference on Robotics and Automation, 2019

Uncertainty-Aware Data Aggregation for Deep Imitation Learning.

Yuchen Cui, David Isele, Scott Niekum, Kikuo Fujimura

Proceedings of the International Conference on Robotics and Automation, 2019

Importance Sampling Policy Evaluation with an Estimated Behavior Policy.

Josiah Hanna, Scott Niekum, Peter Stone

Proceedings of the 36th International Conference on Machine Learning, 2019

Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations.

Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum

Proceedings of the 36th International Conference on Machine Learning, 2019

Enhancing Robot Learning with Human Social Cues.

Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum

Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, 2019

Learning from Corrective Demonstrations.

Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz

Proceedings of the 14th ACM/IEEE International Conference on Human-Robot Interaction, 2019

Understanding Teacher Gaze Patterns for Robot Learning.

Akanksha Saran, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations.

Daniel S. Brown, Wonjoon Goo, Scott Niekum

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications.

Daniel S. Brown, Scott Niekum

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

LAAIR: A Layered Architecture for Autonomous Interactive Robots.

Yuqian Jiang, Nick Walker, Minkyu Kim, Nicolas Brissonneau, Daniel S. Brown, Justin W. Hart, Scott Niekum, Luis Sentis, Peter Stone

CoRR, 2018

Towards Online Learning from Corrective Demonstrations.

Reymundo A. Gutierrez, Elaine Schaertl Short, Scott Niekum, Andrea Lockerd Thomaz

CoRR, 2018

Learning Multi-Step Robotic Tasks from Observation.

Wonjoon Goo, Scott Niekum

CoRR, 2018

Human Gaze Following for Human-Robot Interaction.

Akanksha Saran, Srinjoy Majumdar, Elaine Schaertl Short, Andrea Thomaz, Scott Niekum

Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Incremental Task Modification via Corrective Demonstrations.

Reymundo A. Gutierrez, Vivian Chu, Andrea Lockerd Thomaz, Scott Niekum

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Active Reward Learning from Critiques.

Yuchen Cui, Scott Niekum

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Asking for Help Effectively via Modeling of Human Beliefs.

Taylor Kessler Faulkner, Scott Niekum, Andrea Thomaz

Proceedings of the Companion of the 2018 ACM/IEEE International Conference on Human-Robot Interaction, 2018

Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics.

Ajinkya Jain, Scott Niekum

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Risk-Aware Active Inverse Reinforcement Learning.

Daniel S. Brown, Yuchen Cui, Scott Niekum

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Efficient Probabilistic Performance Bounds for Inverse Reinforcement Learning.

Daniel S. Brown, Scott Niekum

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

Safe Reinforcement Learning via Shielding.

Mohammed Alshiekh, Roderick Bloem, Rüdiger Ehlers, Bettina Könighofer, Scott Niekum, Ufuk Topcu

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Viewpoint selection for visual failure detection.

Akanksha Saran, Branka Lakic, Srinjoy Majumdar, Jürgen Hess, Scott Niekum

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Classification error correction: A case study in brain-computer interfacing.

Hasan A. Poonawala, Mohammed Alshiekh, Scott Niekum, Ufuk Topcu

Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Data-Efficient Policy Evaluation Through Behavior Policy Search.

Josiah P. Hanna, Philip S. Thomas, Peter Stone, Scott Niekum

Proceedings of the 34th International Conference on Machine Learning, 2017

Toward Probabilistic Safety Bounds for Robot Learning from Demonstration.

Daniel S. Brown, Scott Niekum

Proceedings of the 2017 AAAI Fall Symposia, Arlington, Virginia, USA, November 9-11, 2017, 2017

Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation.

Josiah P. Hanna, Peter Stone, Scott Niekum

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

High Confidence Off-Policy Evaluation with Models.

Josiah P. Hanna, Peter Stone, Scott Niekum

CoRR, 2016

On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search.

Piyush Khandelwal, Elad Liebman, Scott Niekum, Peter Stone

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Learning grounded finite-state representations from unstructured demonstrations.

Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Sachin Chitta, Bhaskara Marthi, Andrew G. Barto

Int. J. Robotics Res., 2015

Policy Evaluation Using the Ω-Return.

Philip S. Thomas, Scott Niekum, Georgios Theocharous, George Dimitri Konidaris

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Online Bayesian changepoint detection for articulated motion models.

Scott Niekum, Sarah Osentoski, Christopher G. Atkeson, Andrew G. Barto

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Active articulation model estimation through interactive perception.

Karol Hausman, Scott Niekum, Sarah Osentoski, Gaurav S. Sukhatme

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Learning pouring skills from demonstration and practice.

Akihiko Yamaguchi, Christopher G. Atkeson, Scott Niekum, Tsukasa Ogasawara

Proceedings of the 14th IEEE-RAS International Conference on Humanoid Robots, 2014

2013

Incremental Semantically Grounded Learning from Demonstration.

Scott Niekum, Sachin Chitta, Andrew G. Barto, Bhaskara Marthi, Sarah Osentoski

Proceedings of the Robotics: Science and Systems IX, Technische Universität Berlin, Berlin, Germany, June 24, 2013

An Integrated System for Learning Multi-Step Robotic Tasks from Unstructured Demonstrations.

Scott Niekum

Proceedings of the Designing Intelligent Robots: Reintegrating AI II, 2013

2012

Learning and generalization of complex tasks from unstructured demonstrations.

Scott Niekum, Sarah Osentoski, George Dimitri Konidaris, Andrew G. Barto

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

Complex Task Learning from Unstructured Demonstrations.

Scott Niekum

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning.

George Dimitri Konidaris, Scott Niekum, Philip S. Thomas

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Evolution of reward functions for reinforcement learning.

Scott Niekum, Lee Spector, Andrew G. Barto

Proceedings of the 13th Annual Genetic and Evolutionary Computation Conference, 2011

Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery.

Scott Niekum, Andrew G. Barto

Proceedings of the Lifelong Learning, 2011

2010

Genetic Programming for Reward Function Search.

Scott Niekum, Andrew G. Barto, Lee Spector

IEEE Trans. Auton. Ment. Dev., 2010

Evolved Intrinsic Reward Functions for Reinforcement Learning.

Scott Niekum

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010