2 papers
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.LG2025
Deep Reinforcement Learning with Gradient Eligibility Traces
Esraa Elelimy, Brett Daley, Andrew Patterson +3
Achieving fast and stable off-policy learning in deep reinforcement learning (RL) is challenging. Most existing methods rely on semi-gradient temporal-difference (TD) methods for t…