In this paper, we introduce a novel particle filtering architecture to simulate uncertain emotion generation under multi-stimulus, to enrich emotions for virtual characters. Particles are exploited to predict emotions by sampling possible natural emotional reactions from individuals’ memories and common reactions, and the prediction is subsequently adjusted through likelihood function constructed through appraisals of the cognitive component. Thus this generation process combines the natural reactions and cognitive results of individuals’ into a unified architecture. Furthermore, the expression of emotion as a communicative act is implemented by setting moral standards that an individual must obey, no matter what his or her real emotional reaction is to the stimulus. This generation and expression process is implemented with our uncertain emotion generator under multistimulus system (UEGM).