Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks

Yuqian Jiang, Sudarshanan Bharadwaj, Bo Wu +3

In continuing tasks, average-reward reinforcement learning may be a more appropriate problem formulation than the more common discounted reward formulation. As usual, learning an o…