提出无需传统假设的偏好理论，可统一表示各类决策系统。
Formal Power Series Representations in Probability and Expected Utility Theory
- 用形式幂级数构建新偏好理论，突破传递性等限制
- 任意满足一致性条件的偏好都能扩展为完整系统
- 适用于非连续、无界等复杂决策场景，适合理论研究者
我们提出一种新的相干偏好理论，摆脱了正统理论的诸多限制。该理论表明，只要偏好系统满足某种类似于 de Finetti 概率公理的一致性要求，就可扩展为完整的偏好体系。与 de Finetti 理论不同，本理论不要求偏好具有传递性、阿基米德性、有界性或连续性。此外，任何满足一致性的完整偏好系统，均可通过有序域扩张中的效用函数进行表示。效用可表示性是本文核心结果的推论，该结果同时推广了 Hölder 定理并强化了 Hahn 嵌入定理。
原文摘要 · Abstract (English)
We advance a general theory of coherent preference that surrenders restrictions embodied in orthodox doctrine. This theory enjoys the property that any preference system admits extension to a complete system of preferences, provided it satisfies a certain coherence requirement analogous to the one de Finetti advanced for his foundations of probability. Unlike de Finetti's theory, the one we set forth requires neither transitivity nor Archimedeanness nor boundedness nor continuity of preference. This theory also enjoys the property that any complete preference system meeting the standard of coherence can be represented by utility in an ordered field extension of the reals. Representability by utility is a corollary of this paper's central result, which at once extends Hölder's Theorem and strengthens Hahn's Embedding Theorem.
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