Modeling Acceptable Novelty Based on Bayesian Information

An individual’s acceptance of novelty depends on their emotions. We previously developed mathematical models emotional dimensions associated with novelty, such as arousal (i.e., surprise) and valence positivity negativity). The based Bayesian theorem have three parameters: prediction error, uncertainty external noise. Based Berlyne’s potential, we formulated an inverse U shape function arousal. assume that the level where turns from positive to negative shows range users would accept. In this study, derive a corresponding error term ‘acceptable novelty’. Our model predicts greater uncertainty, larger acceptable novelty. experimental results using musical stimuli novice participants supports under assumption is than By contrast, experts’ result explained by when low