Risk, ambiguity, and misspecification: Decision theory, robust control, and statistics
结合稳健控制理论与统计决策理论，探讨深度不确定性如何影响审慎决策，重新解释决策理论的公理基础以表达对先验和似然函数误设的担忧。
Summary What are “deep uncertainties” and how should their presence influence prudent decisions? To address these questions, we bring ideas from robust control theory into statistical decision theory. Decision theory has its origins in axiomatic formulations by von Neumann and Morgenstern, Wald, and Savage. After Savage, decision theorists constructed axioms that formalize a notion of ambiguity aversion. Meanwhile, control theorists constructed decision rules that are robust to some model misspecifications. We reinterpret axiomatic foundations of decision theories to express ambiguity about a prior over a family of models along with concerns about misspecifications of the corresponding likelihood functions.