Risk measures are commonly used to capture the risk preferences of decision-makers (DMs). The decisions of DMs can be nudged or manipulated when their risk preferences are influenced by factors like the perception of losses and the availability of information about the uncertainties. In this work, we propose a Stackelberg risk preference design (STRIPE) problem to capture a designer's incentive to influence DMs' risk preferences. STRIPE consists of two levels. In the lower-level, individual DMs in a population, known as the followers, respond to uncertainties according to their risk preference types that specify their risk measures. In the upper-level, the leader influences the distribution of the types to induce targeted decisions and steers the follower's preferences to it. Our analysis centers around the solution concept of approximate Stackelberg equilibrium that yields suboptimal behaviors of the players. We show the existence of the approximate Stackelberg equilibrium. The primitive risk perception gap, defined as the Wasserstein distance between the original and the target type distributions, is important in estimating the optimal design cost. We connect the leader's optimality tolerance on the cost with her ambiguity tolerance on the follower's approximate solutions leveraging Lipschitzian properties of the lower-level solution mapping. To obtain the Stackelberg equilibrium, we reformulate STRIPE into a single-level optimization problem using the spectral representations of law-invariant coherent risk measures. We create a data-driven approach for computation and study its performance guarantees. We apply STRIPE to contract design problems to mitigate the intensity of moral hazard. Moreover, we connect STRIPE with meta-learning problems and derive adaptation performance estimates of the meta-parameter using the sensitivity of the optimal value function in the lower-level.
翻译:通常使用风险措施来捕捉决策者(DMs)的风险偏好。当DMs的决定在风险偏好受到损失感和关于不确定性的信息的可得性等因素的影响时,DMs的决定可能会受到操纵或操纵。在这项工作中,我们建议采用Stackelberg风险偏好设计(STRIPE)问题来捕捉设计者影响DMs风险偏好的积极性。STRIPE由两个层次组成。在较低层次,即人口(称为追随者)的单个DMsmodes,根据风险偏好类型对不确定性作出反应,具体规定风险措施。在上层一级,领导影响类型分配以诱导定向决定并引导追随者的偏好。我们的分析中心围绕接近Stackelberg 风险偏好性设计(STRIPE) 问题,我们展示了大约Stakkelbergberg 的平衡。在最初和目标类型分布上的微小风险认识差距,在估计最佳设计成本时很重要。我们将领导人在成本方面的最佳容忍度上采用Slickrickrlial的数值水平上,我们用Slistal-real real deal real real real real real real laction laction rodustration rodustration rodustr