在寻求自我的人类面前重新思考安全控制
Rethinking Safe Control in the Presence of Self-Seeking Humans
摘要：
安全控制方法通常旨在即使在最坏情况下的人为不确定性下也能安全运行。然而，人类可能会利用这种安全第一的系统，这会给每个人带来更大的风险。尽管它们的重要性，没有以前的工作已经调查，并占这些因素在安全控制。在本文中，我们利用博弈论中基于交互的收益结构来模拟人类的短视，自我寻求行为以及人类如何根据先前的经验改变对机器的策略。我们将这些战略性的人类行为整合到一个安全的控制架构中。其结果是，我们的方法实现了更好的安全性和性能的权衡相比，确定性的最坏情况下的安全控制技术和基于平衡的随机方法。我们的研究结果表明，迫切需要从根本上重新思考人与技术互动中使用的安全控制框架，以追求所有人的更大安全。
英文摘要：
Safe control methods are often intended to behave safely even in worst-case human uncertainties. However, humans may exploit such safety-first systems, which results in greater risk for everyone. Despite their significance, no prior work has investigated and accounted for such factors in safe control. In this paper, we leverage an interaction-based payoff structure from game theory to model humans' short-sighted, self-seeking behaviors and how humans change their strategies toward machines based on prior experience. We integrate such strategic human behaviors into a safe control architecture. As a result, our approach achieves better safety and performance trade-offs when compared to both deterministic worst-case safe control techniques and equilibrium-based stochastic methods. Our findings suggest an urgent need to fundamentally rethink the safe control framework used in human-technology interaction in pursuit of greater safety for all.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
