Summary of Experiments in Belief-Space Planning at the Laboratory for Perceptual Robotics. - Scott Michael Jordan; Dirk Ruiken; Tiffany Q. Liu; Takeshi Takahashi 002; Michael William Lanighan; Roderic A. Grupen (AAAI Spring Symposia, 2017)

Learning to Use a Ratchet by Modeling Spatial Relations in Demonstrations. - Li Yang Ku; Scott Michael Jordan; Julia Badger; Erik G. Learned-Miller; Rod Grupen (ISER, 2018)

Distributed Evaluations: Ending Neural Point Metrics. - Daniel Cohen; Scott M. Jordan; W. Bruce Croft (CoRR, 2018)

Learning Action Representations for Reinforcement Learning. - Yash Chandak; Georgios Theocharous; James E. Kostas; Scott M. Jordan; Philip S. Thomas (ICML, 2019)

Learning a Better Negative Sampling Policy with Deep Neural Networks for Search. - Daniel Cohen; Scott M. Jordan; W. Bruce Croft (ICTIR, 2019)

Classical Policy Gradient: Preserving Bellman's Principle of Optimality. - Philip S. Thomas; Scott M. Jordan; Yash Chandak; Chris Nota; James E. Kostas (CoRR, 2019)

Evaluating the Performance of Reinforcement Learning Algorithms. - Scott M. Jordan; Yash Chandak; Daniel Cohen; Mengxue Zhang; Philip S. Thomas (ICML, 2020)

Towards Safe Policy Improvement for Non-Stationary MDPs. - Yash Chandak; Scott M. Jordan; Georgios Theocharous; Martha White; Philip S. Thomas (NeurIPS, 2020)

High Confidence Generalization for Reinforcement Learning. - James E. Kostas; Yash Chandak; Scott M. Jordan; Georgios Theocharous; Philip S. Thomas (ICML, 2021)

Behavior Alignment via Reward Function Optimization. - Dhawal Gupta; Yash Chandak; Scott M. Jordan; Philip S. Thomas; Bruno C. da Silva 001 (NeurIPS, 2023)

Avoiding Model Estimation in Robust Markov Decision Processes with a Generative Model. - Wenhao Yang; Han Wang; Tadashi Kozuno; Scott M. Jordan; Zhihua Zhang (CoRR, 2023)

Coagent Networks: Generalized and Scaled. - James E. Kostas; Scott M. Jordan; Yash Chandak; Georgios Theocharous; Dhawal Gupta; Martha White; Bruno Castro da Silva; Philip S. Thomas (CoRR, 2023)

From Past to Future: Rethinking Eligibility Traces. - Dhawal Gupta; Scott M. Jordan; Shreyas Chaudhari; Bo Liu 006; Philip S. Thomas; Bruno Castro da Silva (AAAI, 2024)

Position: Benchmarking is Limited in Reinforcement Learning Research. - Scott M. Jordan; Adam White 001; Bruno Castro da Silva; Martha White; Philip S. Thomas (ICML, 2024)

The Cliff of Overcommitment with Policy Gradient Step Sizes. - Scott M. Jordan; Samuel Neumann; James E. Kostas; Adam White 001; Philip S. Thomas (RLJ, 2024)

A New View on Planning in Online Reinforcement Learning. - Kevin Roice; Parham Mohammad Panahi; Scott M. Jordan; Adam White 001; Martha White (CoRR, 2024)

Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing. - Bhiman Kumar Baghel; Scott M. Jordan; Zheyuan Ryan Shi; Xiang Lorraine Li (CoRR, 2025)