Efficient Multi-Task Reinforcement Learning via Task-Specific Action Correction

A novel approach called Task-Specific Action Correction (TSAC) decomposes policy learning into two cooperative policies - a shared policy and an action correction policy - to facilitate efficient multi-task reinforcement learning by leveraging goal-oriented sparse rewards.