Prospect Theory (PT) models human decision-making under uncertainty, while epistemic markers (e.g., maybe) serve to express uncertainty in language. However, it remains largely unexplored whether Prospect Theory applies to contemporary Large Language Models and whether epistemic markers, which express human uncertainty, affect their decision-making behaviour. To address these research gaps, we design a three-stage experiment based on economic questionnaires. We propose a more general and precise evaluation framework to model LLMs' decision-making behaviour under PT, introducing uncertainty through the empirical probability values associated with commonly used epistemic markers in comparable contexts. We then incorporate epistemic markers into the evaluation framework based on their corresponding probability values to examine their influence on LLM decision-making behaviours. Our findings suggest that modelling LLMs' decision-making with PT is not consistently reliable, particularly when uncertainty is expressed in diverse linguistic forms. Our code is released in https://github.com/HKUST-KnowComp/MarPT.

翻译：前景理论（PT）用于建模人类在不确定性下的决策行为，而认知标记（如"可能"）则用于表达语言中的不确定性。然而，前景理论是否适用于当代大型语言模型，以及表达人类不确定性的认知标记是否会影响其决策行为，这些问题在很大程度上仍未得到探索。为填补这些研究空白，我们基于经济学问卷设计了一个三阶段实验。我们提出了一个更通用且精确的评估框架，用于建模PT下LLMs的决策行为，通过引入与可比语境中常用认知标记相关的经验概率值来表征不确定性。随后，我们根据相应的概率值将认知标记纳入评估框架，以检验其对LLM决策行为的影响。我们的研究结果表明，使用PT建模LLMs的决策行为并非始终可靠，尤其当不确定性以多样化的语言形式表达时。我们的代码发布于https://github.com/HKUST-KnowComp/MarPT。