← Authors

Scott Niekum

43 papers · 2011–2025 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (9) 🐝 Cross-Pollinator (13) πŸƒ Academic Marathon (14) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) πŸ—ΊοΈ Taxonomy Completionist (23) 🧭 Keyword Pioneer 🀝 Dynamic Duo (10) πŸ† Grand Slam πŸ”¬ Deep Specialist (12) 🧬 Topic Evolution πŸ† Keyword Champion (3) πŸš€ Conference Pioneer πŸ”₯ Unstoppable (11) ⚑ Prolific Year (9) πŸ—ƒοΈ Keyword Collector (63) πŸ’Ž Century Club (43) ❓ The Questioner πŸ“ˆ Trend Setter

Conferences

CORL (10) NIPS (10) ICLR (6) ICML (6) AAAI (4) IJCAI (3) JMLR (2) L4DC (1) RSS (1)

Top co-authors

Peter Stone (10) Philip S. Thomas (7) Harshit Sikchi (6) Amy Zhang (6) W. Bradley Knox (5) Yuchen Cui (5) George Konidaris (3) Stephen Giguere (3) Yash Chandak (3) Wonjoon Goo (3)

Research topics

Learning Paradigms (1) Robotics (1)

Keywords

reinforcement learning (10) imitation learning (7) reward function (5) robot manipulation (5) off-policy evaluation (5) inverse reinforcement learning (4) policy learning (4) policy evaluation (3) reward learning (3) mean squared error (3) behavior policy (3) preference learning (3) deep reinforcement learning (2) skill discovery (2) value estimation (2) markov decision process (2) importance sampling (2) transfer learning (2) robot learning (2) active learning (2)

Papers

An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning ICLR 2025
Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning ICLR 2025
Learning Optimal Advantage from Preferences and Mistaking It for Reward AAAI 2024
Dual RL: Unification and New Methods for Reinforcement and Imitation Learning ICLR 2024
Score Models for Offline Goal-Conditioned Reinforcement Learning ICLR 2024
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning ICLR 2024
Predicting Future Actions of Reinforcement Learning Agents NIPS 2024
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions NIPS 2024
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms NIPS 2024
Data-Efficient Policy Evaluation Through Behavior Policy Search JMLR 2024
A Dual Approach to Imitation Learning from Observations with Offline Datasets CORL 2024
The Perils of Trial-and-Error Reward Design: Misdesign through Overfitting and Invalid Task Specifications AAAI 2023
Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? L4DC 2022
Fairness Guarantees under Demographic Shift ICLR 2022
SCAPE: Learning Stiffness Control from Augmented Position Control Experiences CORL 2021
You Only Evaluate Once: a Simple Baseline Algorithm for Offline RL CORL 2021
Distributional Depth-Based Estimation of Object Articulation Models CORL 2021
Value Alignment Verification ICML 2021
Universal Off-Policy Evaluation NIPS 2021
Demonstration of the EMPATHIC Framework for Task Learning from Implicit Human Feedback AAAI 2021
Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning IJCAI 2021
A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms JMLR 2021
Adversarial Intrinsic Motivation for Reinforcement Learning NIPS 2021
SOPE: Spectrum of Off-Policy Estimators NIPS 2021
Human Gaze Assisted Artificial Intelligence: A Review IJCAI 2020
Safe Imitation Learning via Fast Bayesian Reward Inference from Preferences ICML 2020
PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards CORL 2020
The EMPATHIC Framework for Task Learning from Implicit Human Feedback CORL 2020
Bayesian Robust Optimization for Imitation Learning NIPS 2020
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations ICML 2019
Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations CORL 2019
Understanding Teacher Gaze Patterns for Robot Learning CORL 2019
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications AAAI 2019
Importance Sampling Policy Evaluation with an Estimated Behavior Policy ICML 2019
Using Natural Language for Reward Shaping in Reinforcement Learning IJCAI 2019
Efficient Hierarchical Robot Motion Planning Under Uncertainty and Hybrid Dynamics CORL 2018
Risk-Aware Active Inverse Reinforcement Learning CORL 2018
Data-Efficient Policy Evaluation Through Behavior Policy Search ICML 2017
On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search ICML 2016
Policy Evaluation Using the Ξ©-Return NIPS 2015
Incremental Semantically Grounded Learning from Demonstration RSS 2013
TD_gamma: Re-evaluating Complex Backups in Temporal Difference Learning NIPS 2011
Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery NIPS 2011