主观概率的更优基础
Better Foundations for Subjective Probability
AI总结：
针对标准表征定理依赖强理性假设、无法为非理性智能体归属主观概率的问题，本文提出基于弱理性假设的表征定理，可为部分非理性智能体定义或度量主观概率，夯实主观概率的理论基础。
摘要：
我们如何归属主观概率？在决策论中，这一问题通常通过可追溯至Ramsey（1926）的表征定理来解决，这类定理说明如何通过可观测偏好来定义或度量主观概率。然而，标准表征定理作出了强理性假设，尤其是期望效用最大化假设。我们如何向不满足这些强理性假设的智能体归属主观概率？本文提出了一个具备弱理性假设的表征定理，可用于为部分非理性的智能体定义或度量主观概率。
英文摘要：
How do we ascribe subjective probability? In decision theory, this question is often addressed by representation theorems, going back to Ramsey (1926), which tell us how to define or measure subjective probability by observable preferences. However, standard representation theorems make strong rationality assumptions, in particular expected utility maximization. How do we ascribe subjective probability to agents which do not satisfy these strong rationality assumptions? I present a representation theorem with weak rationality assumptions which can be used to define or measure subjective probability for partly irrational agents.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
