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Theory of Variable Fuzzy Sets for Artificial Emotions Prediction

机译:人工情感预测的可变模糊集理论

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Emotions have a very important impact on human’s beliefs, motivations, actions, and physical states. Emotions predicting and its application in intelligent system can improve the interaction between humans and machines. Current research in artificial emotion focuses on how to measure, calculate, or compute it. However, the transfer of emotion is often too complicated to present full emotion states and changes. This paper combines with emotional dimension and theory of variable fuzzy sets to present a predicting artificial emotion model and shows illustrated example of it. This study shows that any raw data from input can be computed with variable fuzzy set. It provides a mathematical method for representing emotion quantitative, gradual qualitative, and mutated qualitative change. This framework improves calculation methods and mechanisms, closer to real emotional changes.
机译:情绪对人类的信念,动机,行动和身体状态具有非常重要的影响。情绪预测及其在智能系统中的应用可以改善人机交互。当前对人工情感的研究集中于如何测量,计算或计算它。但是,情感的传递通常过于复杂,无法呈现完整的情感状态和变化。本文结合情感维度和可变模糊集理论,提出了一种预测的人工情感模型,并举例说明了该模型。这项研究表明,可以使用可变模糊集来计算输入中的任何原始数据。它提供了一种数学方法来表示情绪的定量,逐渐定性和变异的定性变化。该框架改进了计算方法和机制,更接近真实的情绪变化。

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