Academic Works

Meta-World+: An Improved, Standardized, RL Benchmark

R. McLean, E. Chatzaroulas, L. McCutcheon, F. Röder, T. Yu, Z. He, KR Zentner, R. Julian, J. K. Terry, I. Woungang, N. Farsad, P. Samuel Castro

NeurIPS 2025

Multi-Task Reinforcement Learning Enables Parameter Scaling

R. McLean, E. Chatzaroulas, J. K. Terry, I. Woungang, N. Farsad, P. Samuel Castro

Reinforcement Learning Conference 2025

Outstanding Paper Award on Scientific Understanding in Reinforcement Learning

A2Perf: Real-World Autonomous Agents Benchmark

I. Uchendu, J. Jabbour, K. Van den Berghe, J. Runevic, M. Stewart, J. Ma, S. Krishnan, I. Gur, A. Huang, C. Bishop, P. Bailey, W. Jiang, E. M Songhori, S. Guadarrama, J. Tan, J. K. Terry, A. Faust, V. Janapa Reddi

arXiv 2025

Gymnasium: A Standard Interface for Reinforcement Learning Environments

M. Towers*, A. Kwiatkowski*, J. K. Terry*, J. U. Balis, G. De Cola, T. Deleu, M. Goulão, A. Kallinteris, M. Krimmel, Markus, A. KG, and others

NeurIPS 2024

Spotlight paper

Accepted into AAMAS OptLearnMAS 2021 and NeurIPS Deep RL Workshops

Understanding Generalization Through Visualizations

W. R. Huang, Z. Emam, M. Goldblum, L. Fowl, J. K. Terry, F. Huang, and T. Goldstein

arXiv 2021

Accepted into NeurIPS ICBINB 2020 workshop, spotlight talk

Accepted into AAMAS OptLearnMAS 2021 Workshop

Academic Works

Meta-World+: An Improved, Standardized, RL Benchmark

Multi-Task Reinforcement Learning Enables Parameter Scaling

A2Perf: Real-World Autonomous Agents Benchmark

Gymnasium: A Standard Interface for Reinforcement Learning Environments

MOMAland: A Set of Benchmarks for Multi-Objective Multi-Agent Reinforcement Learning

Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Tasks

Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics

Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments

Revisiting Parameter Sharing in Multi-Agent Deep Reinforcement Learning

PettingZoo: Gym for Multi-Agent Reinforcement Learning

Understanding Generalization Through Visualizations

Statistically Significant Stopping of Neural Network Training

Supersuit: Simple Microwrappers for Reinforcement Learning Environments

Multiplayer Support for the Arcade Learning Environment