一篇新论文讨论了在集成人工智能和机器学习组件的自主系统中确保可靠性所面临的挑战。由于人工智能的不可预测性，传统的安全、安保和可靠性方法已不足以应对。该论文探讨了新的方法和框架，以弥合人工智能创新与可认证的系统级可靠性需求之间的差距。 AI
影响 强调了在安全关键型自主系统中对人工智能进行新的验证和认证方法的必要性。
排序理由 这是一篇讨论人工智能集成在自主系统中的设计挑战的研究论文。
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arXiv:2604.27807v1 Announce Type: new Abstract: The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integrati…
The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integration of intelligent, data-driven components. Ensur…
The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integration of intelligent, data-driven components. Ensur…