2025
Enhancing Online Reinforcement Learning with Meta-Learned Objective from Offline Data
AAAI 2025technical
A major challenge in Reinforcement Learning (RL) is the difficulty of learning an optimal policy from sparse rewards. Prior works enhance online RL with conventional Imitation Learning (IL) via a handcrafted auxiliary objective, at the cost of restricting the RL policy to be sub-optimal when the off…