Understanding Generalization Through Visualizations. - W. Ronny Huang; Zeyad Emam; Micah Goldblum; Liam Fowl; J. K. Terry 001; Furong Huang; Tom Goldstein (ICBINB@NeurIPS, 2020)

Parameter Sharing For Heterogeneous Agents in Multi-Agent Reinforcement Learning. - J. K. Terry 001; Nathaniel Grammel; Sanghyun Son 003; Benjamin Black (CoRR, 2020)

SuperSuit: Simple Microwrappers for Reinforcement Learning Environments. - J. K. Terry 001; Benjamin Black; Ananth Hari (CoRR, 2020)

Multiplayer Support for the Arcade Learning Environment. - J. K. Terry 001; Benjamin Black (CoRR, 2020)

PettingZoo: Gym for Multi-Agent Reinforcement Learning. - J. K. Terry 001; Benjamin Black; Ananth Hari; Luis S. Santos; Clemens Dieffendahl; Niall L. Williams; Yashas Lokesh; Caroline Horsch; Praveen Ravi (CoRR, 2020)

PettingZoo: Gym for Multi-Agent Reinforcement Learning. - J. K. Terry 001; Benjamin Black; Nathaniel Grammel; Mario Jayakumar; Ananth Hari; Ryan Sullivan; Luis S. Santos; Clemens Dieffendahl; Caroline Horsch; Rodrigo Perez-Vicente; Niall L. Williams; Yashas Lokesh; et al. (NeurIPS, 2021)

Statistically Significant Stopping of Neural Network Training. - J. K. Terry 001; Mario Jayakumar; Kusal De Alwis (CoRR, 2021)

Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments. - Ryan Sullivan; J. K. Terry 001; Benjamin Black; John P. Dickerson (ICML, 2022)

Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics. - Jun Jet Tai; Jordan K. Terry; Mauro Sebastián Innocente; James Brusey; Nadjim Horri (CoRR, 2022)

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. - Maxime Chevalier-Boisvert; Bolun Dai; Mark Towers; Rodrigo Perez-Vicente; Lucas Willems; Salem Lahlou; Suman Pal; Pablo Samuel Castro; Jordan K. Terry (NeurIPS, 2023)

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks. - Maxime Chevalier-Boisvert; Bolun Dai; Mark Towers; Rodrigo de Lazcano; Lucas Willems; Salem Lahlou; Suman Pal; Pablo Samuel Castro; Jordan K. Terry (CoRR, 2023)

Multi-Agent Reinforcement Learning: Systems for Evaluation and Applications to Complex Systems. - Jordan K. Terry (2023)

MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning. - Florian Felten; Umut Ucak; Hicham Azmani; Gao Peng; Willem Röpke; Hendrik Baier; Patrick Mannion; Diederik M. Roijers; Jordan K. Terry; El-Ghazali Talbi; Grégoire Danoy; Ann Nowé; et al. (CoRR, 2024)

Meta-World+: An Improved, Standardized, RL Benchmark. - Reginald McLean; Evangelos Chatzaroulas; Luc McCutcheon; Frank Röder; Tianhe Yu; Zhanpeng He; K. R. Zentner; Ryan Julian; J. K. Terry 001; Isaac Woungang; Nariman Farsad; Pablo Samuel Castro (NeurIPS, 2025)

Gymnasium: A Standard Interface for Reinforcement Learning Environments. - Mark Towers; Ariel Kwiatkowski; John U. Balis; Gianluca De Cola; Tristan Deleu; Manuel Goulão; Andreas Kallinteris; Markus Krimmel; Arjun KG; Rodrigo Perez-Vicente; J. K. Terry 001; Andrea Pierré; et al. (NeurIPS, 2025)

A2Perf: Real-World Autonomous Agents Benchmark. - Ikechukwu Uchendu; Jason Jabbour; Korneel Van den Berghe; Joel Runevic; Matthew Stewart; Jeffrey Jian Ma; Srivatsan Krishnan; Izzeddin Gur; Austin Huang; Colton Bishop; Paige Bailey; Wenjie Jiang 001; et al. (CoRR, 2025)

Multi-Task Reinforcement Learning Enables Parameter Scaling. - Reginald McLean; Evangelos Chatzaroulas; J. K. Terry 001; Isaac Woungang; Nariman Farsad; Pablo Samuel Castro (CoRR, 2025)