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Anas Aburaya

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Open access 2026

GCR-RL: Gradient Control Reward Shaping for Reinforcement Learning

This work introduces Gradient Control Rewards (GCR), an interpretable, control-inspired reward-design methodology for accelerating agent training by modulating the reward signal based on the temporal dynamics of system error, Inspired by classical control theory.

Anas Aburaya, H. Selamat, M. Muslim et al. · IEEE Access · 0 citations