Autonomous driving paper index
Computational Goal Verification Theory (CGVT)
One-line summary
This paper introduces Computational Goal Verification Theory (CGVT), a unified framework that simultaneously verifies the correctness of a program and the feasibility of the goals it is intended to achieve.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
This paper introduces Computational Goal Verification Theory (CGVT), a unified framework that simultaneously verifies the correctness of a program and the feasibility of the goals it is intended to achieve. CGVT formalizes the relationship between a goal specification G, a program P, and the system environment E, and provides a systematic procedure for checking whether a given program can realistically meet a specified goal under the constraints of its environment. The core idea is two‑fold: first, program verification ensures that P implements the intended functionality; second, goal verification confirms that the target objective G is well‑posed and attainable. By integrating these two aspects, CGVT aims to provide a rigorous foundation for trustworthy artificial intelligence and other complex software systems. The theory is presented with formal definitions, soundness and completeness results, and illustrative case studies in autonomous driving, medical diagnosis, and energy management. Potential implications for AI safety and the pursuit of a Turing Award are discussed, along with directions for future research.
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