Goals play an important role in human cognition. Different aspects of human mind influence the generation of goals they pursue, and the goals guide their behaviors. In psychology, researchers made significant efforts to study goals and their origin, and cognitive architectures include various facilities to handle the goals of artificial agents. One such architecture, ICARUS, supports goal-driven behaviors while maintaining reactivity, and its top-level goals play an important role of guiding the behavior of the agents. However, the architecture covers neither the origin of its top-level goals nor the dynamic aspects of them, and this imposes various restrictions like limited autonomy on ICARUS. In this paper, we extend the architecture to provide the capability to nominate top-level goals using the notion of long-term, general goals, and manage the nominated goals by prioritizing them. For prioritization of goals, we introduce a novel capability to match concepts in a continuous ma...