A fuzzy appraisal model for affective agents adapted to cultural environments using the pleasure and arousal dimensions

Humans use rather vague and imprecise words to express emotions. Therefore, fuzzy logic allows computational affective models to use emotions in the same way that human beings express them. However, people from different cultures and languages assign different meanings to the same emotion word. Unfortunately, there are still no affective computing models that really take these two factors into consideration. In this paper, we propose a fuzzy model of appraisal for multi-agent systems that is adapted to Spanish-speakers. Our methodology has two steps. First, the agent evaluates an event using a set of fuzzy appraisal rules that returns a fuzzy emotion. Then, a defuzzification process returns the Pleasure and Arousal dimensions of the emotion that will be internally represented as a vector in a two-dimensional space. This vector is used to update the agent's mood according to the agent's personality. The agent can express this internal emotional state using a fuzzification process that translates the agent's mood into a fuzzy emotion. This fuzzification process uses the results of an experiment to generate a fuzzy emotion that is adapted to the cultural environment in which the agent is located. This methodology can be easily adapted to other languages. (C) 2020 Elsevier Inc. All rights reserved.

Automated summary

Fuzzy logic enables computational affective models to utilize emotions, but people from different cultures and languages may assign diverse meanings to the same emotion word. This study proposes a fuzzy model tailored for Spanish-speakers, allowing agents to update their emotional states while evaluating events.