情绪习惯对新奇性的数学模型--贝叶斯更新和信息论建模
Mathematical Model of Emotional Habituation to Novelty: Modeling with Bayesian Update and Information Theory
摘要：
新颖性是产品设计创造力的重要因素。然而，对新奇事物的接受取决于一个人的情绪。最后一位作者Yanagisawa和他的同事之前开发了一个与新奇感相关的情感维度的数学模型，如唤醒（惊喜）和效价。该模型基于Berlyne的唤醒电位理论，将唤醒形式化为贝叶斯信息增益和效价作为唤醒的函数。一个人通过反复接触新鲜事物而变得习惯。这种所谓的对新奇事物的习惯在长期产品体验的设计中很重要。在此，我们提出了一个数学模型的基础上的情感维度模型的新颖性习惯化。我们正式的习惯作为一个递减的信息增益从一个新的事件，通过贝叶斯更新。我们从重复暴露的新刺激获得的信息作为三个参数的函数：初始预测误差，初始不确定性和感官刺激的噪声。通过该模型，我们发现了初始预测误差和初始不确定性对习惯化的交互作用。此外，我们证明了一系列的预测误差的积极情绪转向变得更加新颖的重复曝光。
英文摘要：
Novelty is an important factor of creativity in product design. Acceptance of novelty, however, depends on one's emotions. Yanagisawa, the last author, and his colleagues previously developed a mathematical model of emotional dimensions associated with novelty such as arousal (surprise) and valence. The model formalized arousal as Bayesian information gain and valence as a function of arousal based on Berlyne's arousal potential theory. One becomes accustomed to novelty by repeated exposure. This so-called habituation to novelty is important in the design of long-term product experience. We herein propose a mathematical model of habituation to novelty based on the emotional dimension model. We formalized the habituation as a decrement in information gain from a novel event through Bayesian update. We derived the information gained from the repeated exposure of a novel stimulus as a function of three parameters: initial prediction error, initial uncertainty, and noise of sensory stimulus. With the proposed model, we discovered an interaction effect of the initial prediction error and initial uncertainty on habituation. Furthermore, we demonstrate that a range of positive emotions on prediction errors shift toward becoming more novel by repeated exposure.
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