论文标题
从认知到计算建模：基于文本的风险决策，以模糊痕迹理论为指导
From Cognitive to Computational Modeling: Text-based Risky Decision-Making Guided by Fuzzy Trace Theory
论文作者
论文摘要
由于固有的个体差异和非理性性，理解，建模和预测人类风险决策的决策是具有挑战性的。模糊痕量理论（FTT）是一种强大的范式，通过结合GIST，即信息的模糊表示来解释人类的决策，这些信息仅捕获其典型的含义。受Broniatowski和Reyna的FTT认知模型的启发，我们提出了一个计算框架，该计算框架结合了基础语义和情感对基于文本决策的影响。特别是，我们介绍了2类矢量，以学习分类的要点和分类情感，并演示如何优化我们的计算模型以预测群体和个人的危险决策。
Understanding, modelling and predicting human risky decision-making is challenging due to intrinsic individual differences and irrationality. Fuzzy trace theory (FTT) is a powerful paradigm that explains human decision-making by incorporating gists, i.e., fuzzy representations of information which capture only its quintessential meaning. Inspired by Broniatowski and Reyna's FTT cognitive model, we propose a computational framework which combines the effects of the underlying semantics and sentiments on text-based decision-making. In particular, we introduce Category-2-Vector to learn categorical gists and categorical sentiments, and demonstrate how our computational model can be optimised to predict risky decision-making in groups and individuals.
