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Sufficiency of Zeroth-Order Reward Shaping for Policy Gradient in Stabilization Control
Reward shaping is fundamental to modern robotic control with deep reinforcement learning (RL), yet practitioners still rely heavily on heuristic principles borrowed from classical optimal control and trajectory optimization. Existing methods rarely distinguish reward terms that are intrinsic to the
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