Jordan K. Terry

According to our database, Jordan K. Terry authored at least 10 papers between 2022 and 2025.

Collaborative distances:

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

2025

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

Reginald McLean, Evangelos Chatzaroulas, Luc McCutcheon, Frank Röder, Tianhe Yu, Zhanpeng He, K. R. Zentner, Ryan Julian, Jordan K. Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro

CoRR, May, 2025

Multi-Task Reinforcement Learning Enables Parameter Scaling.

Reginald McLean, Evangelos Chatzaroulas, Jordan K. Terry, Isaac Woungang, Nariman Farsad, Pablo Samuel Castro

CoRR, March, 2025

A2Perf: Real-World Autonomous Agents Benchmark.

Ikechukwu Uchendu, Jason Jabbour, Korneel Van den Berghe, Joel Runevic, Matthew Stewart, Jeffrey Ma, Srivatsan Krishnan, Izzeddin Gur, Austin Huang, Colton Bishop, Paige Bailey, Wenjie Jiang, Ebrahim M. Songhori, Sergio Guadarrama, Jie Tan, Jordan K. Terry, Aleksandra Faust, Vijay Janapa Reddi

CoRR, March, 2025

2024

Gymnasium: A Standard Interface for Reinforcement Learning Environments.

Mark Towers, Ariel Kwiatkowski, Jordan K. Terry, John U. Balis, Gianluca De Cola, Tristan Deleu, Manuel Goulão, Andreas Kallinteris, Markus Krimmel, Arjun KG, Rodrigo Perez-Vicente, Andrea Pierré, Sander Schulhoff, Jun Jet Tai, Hannah Tan, Omar G. Younis

CoRR, 2024

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, Roxana Radulescu

CoRR, 2024

2023

Multi-Agent Reinforcement Learning: Systems for Evaluation and Applications to Complex Systems.

Jordan K. Terry

PhD thesis, 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

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Cliff Diving: Exploring Reward Surfaces in Reinforcement Learning Environments.

Ryan Sullivan, Jordan K. Terry, Benjamin Black, John P. Dickerson

Proceedings of the International Conference on Machine Learning, 2022