这学术研究提出新风险度量法，用最优传输球替代旧模式，应对环境变化更高效，和传统方法比能覆盖更多风险点。
该研究提出Wasserstein entropic value - at - risk新风险度量方法，用于处理环境不确定性下的决策问题；该方法以最优传输球为基础，替代传统的相对熵球，能覆盖传统方法忽略的可达灾难场景；它具备变分对偶结构，与经典公式在形式上相互呼应，确保计算计算的严谨性；通过信念熵调节传输半径后，可得到闭合形式的动态规划算子，实现安全边界的收缩与切换。
Robust Risk Under Evolving Uncertainty: A Wasserstein Counterpart of the Entropic Value-at-Risk
An agent still learning its environment should be cautious while ignorant and bold once confident. The entropic value-at-risk captures this through a robust-optimization identity---a confidence level fixes the radius of a relative-entropy ball of alternative models---but that ball cannot reach catastrophes the nominal deems impossible, precisely what a safe agent must hedge. We instead use an optimal-transport ball and study the coherent risk measure it induces, the Wasserstein entropic value-at-risk. It has a variational dual mirroring the entropic formula (an inverse temperature becomes a transport price), occupies a definite place in the risk hierarchy, and provably accounts for the reachable catastrophes the entropic measure ignores; we verify both dualities numerically. Driving the transport radius by belief entropy then yields a closed-form robust dynamic-programming operator whose caution contracts as the belief sharpens, with a certified safety sandwich and a sharp safety switch.