Enhancing RL Safety with Counterfactual LLM Reasoning
<|reference_start|>Enhancing RL Safety with Counterfactual LLM Reasoning: Reinforcement learning (RL) policies may exhibit unsafe behavior and are hard to explain. We use counterfactual large language model reasoning to enhance RL policy safety post-training. We show that our approach improves and helps to explain the RL policy safety.<|reference_end|>
@article{gross2024enhancing,
    title={Enhancing RL Safety with Counterfactual LLM Reasoning},
    author={Dennis Gross and Helge Spieker},
    journal={arXiv preprint arXiv:2409.10188},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.10188},
    primaryClass={cs.LG}
}