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cs.LG2026
Forager: a lightweight testbed for continual learning with partial observability in RL
Steven Tang, Xinze Xiong, Anna Hakhverdyan +7
In continual reinforcement learning (CRL), good performance requires never-ending learning, acting, and exploration in a big, partially observable world. Most CRL experiments have…
cs.LG2024★ 2 cited
A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
Jacob Adkins, Michael Bowling, Adam White
The performance of modern reinforcement learning algorithms critically relies on tuning ever-increasing numbers of hyperparameters. Often, small changes in a hyperparameter can lea…