긍정적 감정에 따른 선언적 지식에 관한 비전형적 연상 과정에 대한 인지모델링

Abstract

The aim of this study was to model unusual association with declarative knowledge by positive affect using ACT-R cognitive architecture. Existing research related with cognitive modeling tends to pay a lot of attentionto strong and negative cognitive moderator. Mild positive affect, however, has far-reaching effects on problem solving and decision making. Typically, subjects with positive affect were more likely to respond to unusualassociates in a word association task than subjects with neutral affect. In this study, a cognitive model using ACT-R cognitive architecture was developed to show the effect of positive affect on the cognitive organizationrelated with memory. First, we organized the memory structure of stimulus word ‘palm’ based on published results in a word association task. Then, we decreased an ACT-R parameter that reflects the amount of weighting given to the dissimilarity between the stimulus word and the associate word to represent reorganized memory structure of the model by positive affect. As a result, no significant associate probability difference between model prediction and existing empirical data was found. The ACT-R cognitive architecture could be used to model the effect of positive affect on the unusual association by decreasing (manipulating) the weight of the dissimilarity. This study is useful in conducting model-based evaluation of the effects of positive affect in complex tasks involving memory, such as creative problem solving.