most citedHuman-centric Reward Optimization for Reinforcement Learning-based Automated Driving using Large Language Models

2 citations · 2 across the 1 of their papers we have counts for

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cs.AI2024★ 2 cited

Human-centric Reward Optimization for Reinforcement Learning-based Automated Driving using Large Language Models

Ziqi Zhou, Jingyue Zhang, Jingyuan Zhang +4

One of the key challenges in current Reinforcement Learning (RL)-based Automated Driving (AD) agents is achieving flexible, precise, and human-like behavior cost-effectively. This…